Paper Digest: IJCAI 2013 Highlights
International Joint Conference on Artificial Intelligence (IJCAI) is one of the top artificial intelligence conferences in the world. In 2013, it is to be held in Beijing, China.
To help the community quickly catch up on the work presented in this conference, Paper Digest Team processed all accepted papers, and generated one highlight sentence (typically the main topic) for each paper. Readers are encouraged to read these machine generated highlights / summaries to quickly get the main idea of each paper.
If you do not want to miss any interesting academic paper, you are welcome to sign up our free daily paper digest service to get updates on new papers published in your area every day. You are also welcome to follow us on Twitter and Linkedin to get updated with new conference digests.
Paper Digest Team
team@paperdigest.org
TABLE 1: IJCAI 2013 Papers
| Title | Authors | Highlight | |
|---|---|---|---|
| 1 | Computational Perspectives on Social Phenomena at Global Scales | Jon Kleinberg | We discuss a set of basic questions that arise in the design and analysis of systems supporting on-line social interactions, focusing on two main issues: the role of network structure in the dynamics of social media sites, and the analysis of textual data as a way to study properties of on-line social interaction. |
| 2 | Soft Robotics: The Next Generation of Intelligent Machines | Rolf Pfeifer, Hugo Gravato Marques, Fumiya Iida | In this article, we put forward some of the properties that will characterize these new robots: soft materials, flexible and stretchable sensors, modular and efficient actuators, self-organization and distributed control. |
| 3 | Computational Disaster Management | Pascal Van Hentenryck | This talk presents some of the progress accomplished in the last 5 years and deployed to assist the response to hurricanes such as Irene and Sandy. |
| 4 | Reasoning about Normative Update | Natasha Alechina, Mehdi Dastani, Brian Logan | We consider the problem of updating a multi-agent system with a set of conditional norms. |
| 5 | Undecidability in Epistemic Planning | Guillaume Aucher, Thomas Bolander | Dynamic epistemic logic (DEL) provides a very expressive framework for multi-agent planning that can deal with nondeterminism, partial observability, sensing actions, and arbitrary nesting of beliefs about other agents’ beliefs. |
| 6 | Maximal Recursive Rule: A New Social Decision Scheme | Haris Aziz | We present a new generalization of random dictatorship for indifferences called Maximal Recursive (MR) rule as an alternative to RSD. |
| 7 | Audit Games | Jeremiah Blocki, Nicolas Christin, Anupam Datta, Ariel D. Procaccia, Arunesh Sinha | We present an audit game model that is a natural generalization of a standard security game model for resource allocation with an additional punishment parameter. |
| 8 | Using Double-Oracle Method and Serialized Alpha-Beta Search for Pruning in Simultaneous Move Games | Branislav Bosansky, Viliam Lisy , Jiri Cermák, Roman Vítek, Michal Pechoucek | We solve these games by a novel algorithm that relies on two components: (1) it iteratively solves the games that correspond to a single simultaneous move using a double-oracle method, and (2) it prunes the states of the game using bounds on the sub-game values obtained by the classical Alpha-Beta search on a serialized variant of the game. |
| 9 | Externalities in Cake Cutting | Simina Branzei, Ariel D. Procaccia, Jie Zhang | We extend the classical model to capture externalities, and generalize the classical fairness notions of proportionality and envy-freeness. |
| 10 | Are There Any Nicely Structured Preference Profiles Nearby? | Robert Bredereck, Jiehua Chen, Gerhard J. Woeginger | We investigate the problem of deciding whether a given preference profile is close to a nicely structured preference profile of a certain type, as for instance single-peaked, single-caved, single-crossing, value-restricted, best-restricted, worst-restricted, medium-restricted, or group-separable profiles. |
| 11 | Conditional Restricted Boltzmann Machines for Negotiations in Highly Competitive and Complex Domains | Siqi Chen, Haitham Bou Ammar, Karl Tuyls, Gerhard Weiss | This paper proposes two novel opponent modeling techniques based on deep learning methods. |
| 12 | Kemeny Elections with Bounded Single-Peaked or Single-Crossing Width | Denis Cornaz, Lucie Galand, Olivier Spanjaard | This paper is devoted to complexity results regarding specific measures of proximity to single-peakedness and single-crossingness, called "single-peaked width" [Cornaz et al., 2012] and "single-crossing width". |
| 13 | Intention-Aware Routing to Minimise Delays at Electric Vehicle Charging Stations | Mathijs M. de Weerdt, Enrico H. Gerding, Sebastian Stein, Valentin Robu, Nicholas R. Jennings | We achieve this by extending existing time-dependent stochastic routing algorithms to include the battery’s state of charge and charging stations. |
| 14 | Optimally Solving Dec-POMDPs as Continuous-State MDPs | Jilles Steeve Dibangoye, Christopher Amato, Olivier Buffet, François Charpillet | By combining a general search algorithm and dimension reduction based on feature selection, we introduce a novel approach to optimally solve problems with significantly longer planning horizons than previous methods. |
| 15 | Elicitation and Approximately Stable Matching with Partial Preferences | Joanna Drummond, Craig Boutilier | We propose the use of maximum regret to measure the (inverse) degree of stability of a matching with partial preferences; minimax regret to find matchings that are maximally stable in the presence of partial preferences; and heuristic elicitation schemes that use max regret to determine relevant preference queries. |
| 16 | C-Link: A Hierarchical Clustering Approach to Large-Scale Near-Optimal Coalition Formation | Alessandro Farinelli, Manuele Bicego, Sarvapali Ramchurn, Mauro Zucchelli | In this paper we address the specific problem of coalition structure generation, and focus on providing good-enough solutions using a novel heuristic approach that is based on data clustering methods. |
| 17 | Control in the Presence of Manipulators: Cooperative and Competitive Cases | Zack Fitzsimmons, Edith Hemaspaandra, Lane A. Hemaspaandra | In this paper, we study the complexity of control attacks on elections in which there are manipulators. |
| 18 | Action Translation in Extensive-Form Games with Large Action Spaces: Axioms, Paradoxes, and the Pseudo-Harmonic Mapping | Sam Ganzfried, Tuomas Sandholm | We present a new mapping that satisfies these desiderata and has significantly lower exploitability than the prior mappings. |
| 19 | Bargaining for Revenue Shares on Tree Trading Networks | Arpita Ghosh, Satyen Kale, Kevin Lang, Benjamin Moseley | In this paper, we investigate how these revenue shares might be set via a natural bargaining process between agents on the tree, specifically, egalitarian bargaining between endpoints of each edge in the tree. |
| 20 | A Matroid Approach to the Worst Case Allocation of Indivisible Goods | Laurent Gourvès, Jérôme Monnot, Lydia Tlilane | A deterministic algorithm returning such an allocation in polynomial time was proposed in [Markakis, E., & Psomas, C. A. (2011). |
| 21 | Audience-Based Uncertainty in Abstract Argument Games | Davide Grossi, Wiebe van der Hoek | The paper generalizes abstract argument games to cope with cases where proponent and opponent argue in front of an audience whose type is known only with uncertainty. |
| 22 | Optimal Airline Ticket Purchasing Using Automated User-Guided Feature Selection | William Groves, Maria Gini | To address this problem, we introduce an automated agent which is able to optimize purchase timing on behalf of customers and provide performance estimates of its computed action policy based on past performance. |
| 23 | Revenue Maximization via Hiding Item Attributes | Mingyu Guo, Argyrios Deligkas | We study probabilistic single-item second-price auctions where the item is characterized by a set of attributes. |
| 24 | Opponent Modelling in Persuasion Dialogues | Christos Hadjinikolis, Yiannis Siantos, Sanjay Modgil, Elizabeth Black, Peter McBurney | In this work, we rely on an agent’s experience to define a mechanism for augmenting an opponent model with information likely to be dialectally related to information already contained in it. |
| 25 | Sequential Equilibrium in Computational Games | Joseph Y. Halpern, Rafael Pass | We examine sequential equilibrium in the context of computational games [Halpern and Pass, 2011a], where agents are charged forcomputation. |
| 26 | Why Is It So Hard to Say Sorry? Evolution of Apology with Commitments in the Iterated Prisoner’s Dilemma | The Anh Han, Luís Moniz Pereira, Francisco C. Santos, Tom Lenaerts | Here we provide a computational model showing that apologizing acts are rare in non-committed interactions, especially whenever cooperation is very costly, and that arranging prior commitments can considerably increase the frequency of such behavior. |
| 27 | The Dynamics of Reinforcement Social Learning in Cooperative Multiagent Systems | Jianye Hao, Ho-fung Leung | To this end, we investigate the multiagent coordination problems in cooperative environments under the social learning framework. |
| 28 | Macau: A Basis for Evaluating Reputation Systems | Christopher J. Hazard, Munindar P. Singh | We present a common conceptual interface for reputation systems and a set of four measurable desiderata that are broadly applicable across multiple domains. |
| 29 | How to Change a Group’s Collective Decision? | Noam Hazon, Raz Lin, Sarit Kraus | In this paper we present four problems that address issues of minimality and safety of the persuasion process. |
| 30 | A Game-Theoretic Machine Learning Approach for Revenue Maximization in Sponsored Search | Di He, Wei Chen, Liwei Wang, Tie-Yan Liu | In this paper, we propose a novel game-theoretic machine learning} approach, which naturally combines machine learning and game theory, and learns the auction mechanism using a bilevel optimization framework. |
| 31 | A Framework to Choose Trust Models for Different E-Marketplace Environments | Athirai A. Irissappane, Siwei Jiang, Jie Zhang | We propose a novel framework to choose suitable trust models for unknown environments, based on the intuition that if a model performs well in one environment, it will do so in another similar environment. |
| 32 | Defender (Mis)Coordination in Security Games | Albert Xin Jiang, Ariel D. Procaccia, Yundi Qian, Nisarg Shah, Milind Tambe | Our goal is to quantify the loss incurred by miscoordination between defenders, both theoretically and empirically. |
| 33 | A Social Welfare Optimal Sequential Allocation Procedure | Thomas Kalinowski, Nina Narodytska, Toby Walsh | We consider a simple sequential allocation procedure for sharing indivisible items between agents in which agents take turns to pick items. |
| 34 | An Intelligent Broker Agent for Energy Trading: An MDP Approach | Rodrigue T. Kuate, Minghua He, Maria Chli, Hai H. Wang | This paper details the development and evaluation of AstonTAC, an energy broker that successfully participated in the 2012 Power Trading Agent Competition (Power TAC). |
| 35 | Agent Failures in All-Pay Auctions | Yoad Lewenberg, Omer Lev, Yoram Bachrach, Jeffrey S. Rosenschein | We model such failures and show how they affect the equilibrium state, revealing various properties, such as the lack of influence of the most-likely-to-participate player on the behavior of the other players. |
| 36 | Efficient Learning in Linearly Solvable MDP Models | Ang Li, Paul R. Schrater | In this research, we develop a robust learning approach to linearly solvable MDPs. |
| 37 | Game-Theoretic Question Selection for Tests | Yuqian Li, Vincent Conitzer | In this paper, we take the loss of confidentiality as a fact. |
| 38 | Multi-Winner Social Choice with Incomplete Preferences | Tyler Lu, Craig Boutilier | We analyze the complexity of this problem and develop new exact and greedy robust optimization algorithms for its solution. |
| 39 | An Ambiguity Aversion Framework of Security Game under Ambiguities | Wenjun Ma, Xudong Luo, Weiru Liu | To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. |
| 40 | Multi-Agent Team Formation: Diversity Beats Strength? | Leandro Soriano Marcolino, Albert Xin Jiang, Milind Tambe | We propose a new model to address these questions. |
| 41 | Control Complexity of Schulze Voting | Curtis Menton, Preetjot Singh | We resolve the complexity of many electoral control cases for Schulze voting. |
| 42 | Computational Analysis of Connectivity Games with Applications to the Investigation of Terrorist Networks | Tomasz P. Michalak, Talal Rahwan, Nicholas R. Jennings, Piotr L. Szczepanski, Oskar Skibski, Ramasuri Narayanam, Michael J. Wooldridge | In this paper, we present the first computational analysis of this class of coalitional games, and propose two algorithms for computing Lindelauf et al.’s centrality metric. |
| 43 | Sufficient Plan-Time Statistics for Decentralized POMDPs | Frans A. Oliehoek | The paper investigates the practical implications, as well as the effectiveness of a new pruning technique for MAA* methods, in a number of benchmark problems and discusses future avenues of research opened by these contributions. |
| 44 | Efficient Vote Elicitation under Candidate Uncertainty | Joel Oren, Yuval Filmus, Craig Boutilier | We analyze the ability of top-k vote elicitation to correctly determine true winners, with high probability, given probabilistic models of voter preferences and candidate availability. |
| 45 | A Proof-Theoretical View of Collective Rationality | Daniele Porello | In this paper, we are interested in analysing the notion of rational outcome by proposing a proof-theoretical understanding of collective rationality. |
| 46 | Coalitional Games via Network Flows | Talal Rahwan, Tri-Dung Nguyen, Tomasz P. Michalak, Maria Polukarov, Madalina Croitoru, Nicholas R. Jennings | We introduce a new representation scheme for coalitional games, called coalition-flow networks (CF-NETs), where the formation of effective coalitions in a task-based setting is reduced to the problem of directing flow through a network. |
| 47 | Opponent Models with Uncertainty for Strategic Argumentation | Tjitze Rienstra, Matthias Thimm, Nir Oren | Using such models, we present three approaches to reasoning. |
| 48 | Efficient Interdependent Value Combinatorial Auctions with Single Minded Bidders | Valentin Robu, David C. Parkes, Takayuki Ito, Nicholas R. Jennings | We study the problem of designing efficient auctions where bidders have interdependent values; i.e., values that depend on the signals of other agents. |
| 49 | Efficiently Solving Joint Activity Based Security Games | Eric Shieh, Manish Jain, Albert Xin Jiang, Milind Tambe | To address this challenge, this paper presents two branch-and-price algorithms for solving SSGs, SMARTO and SMARTH, with three novel features: (i) a column-generation approach that uses an ordered network of nodes (determined by solving the traveling salesman problem) to generate individual defender strategies; (ii) exploitation of iterative reward shaping of multiple coordinating defender units to generate coordinated strategies; (iii) generation of tighter upper-bounds for pruning by solving security games that only abide by key scheduling constraints. |
| 50 | Fully Proportional Representation as Resource Allocation: Approximability Results | Piotr Skowron, Piotr Faliszewski, Arkadii Slinko | We show good approximation algorithms for the satisfaction-based utilitarian cases, and inapproximability results for the remaining settings. |
| 51 | Bimodal Switching for Online Planning in Multiagent Settings | Ekhlas Sonu, Prashant Doshi | We present a bimodal method for online planning in partially observable multiagent settings as formalized by a finitely-nested interactive partially observable Markov decision process (I-POMDP). |
| 52 | Analysis and Optimization of Multi-Dimensional Percentile Mechanisms | Xin Sui, Craig Boutilier, Tuomas Sandholm | More importantly, we propose a sample-based framework for optimizing the choice of percentiles relative to any prior distribution over preferences, while maintaining strategy-proofness. |
| 53 | Multi-Dimensional Single-Peaked Consistency and Its Approximations | Xin Sui, Alex Francois-Nienaber, Craig Boutilier | In this article, we assess the ability of both single-dimensional and multi-dimensional approximations to explain preference profiles drawn from several real-world elections. |
| 54 | An Efficient Vector-Based Representation for Coalitional Games | Long Tran-Thanh, Tri-Dung Nguyen, Talal Rahwan, Alex Rogers, Nicholas R. Jennings | We propose a new representation for coalitional games, called the coalitional skill vector model, where there is a set of skills in the system, and each agent has a skill vector — a vector consisting of values that reflect the agents’ level in different skills. |
| 55 | Endogenous Boolean Games | Paolo Turrini | We analyze equilibria in EBGs, showing the preconditions needed for desirable outcomes to be achieved without external intervention. |
| 56 | Monte-Carlo Expectation Maximization for Dec-POMDPs | Feng Wu, Shlomo Zilberstein, Nicholas R. Jennings | We introduce a model-free version of this approach that employs Monte-Carlo EM(MCEM). |
| 57 | Scaling-Up Security Games with Boundedly Rational Adversaries: A Cutting-Plane Approach | Rong Yang, Albert Xin Jiang, Milind Tambe, Fernando Ordóñez | To improve the current real-world deployments of Stackelberg security games (SSGs), it is critical now to efficiently incorporate models of adversary bounded rationality in large-scale SSGs. |
| 58 | Automated Generation of Interaction Graphs for Value-Factored Decentralized POMDPs | William Yeoh, Akshat Kumar, Shlomo Zilberstein | In this paper, we introduce three algorithms to automatically generate interaction graphs for models within the VF framework and establish lower and upper bounds on the expected reward of an optimal joint policy. |
| 59 | A Reputation Management Approach for Resource Constrained Trustee Agents | Han Yu, Chunyan Miao, Bo An, Cyril Leung, Victor R. Lesser | To mitigate this problem, we propose a reputation management approach for trustee agents based on distributed constraint optimization. |
| 60 | Multiwinner Elections under Preferences that Are Single-Peaked on a Tree | Lan Yu, Hau Chan, Edith Elkind | For the standard (utilitarian) version of this problem we provide an algorithm for an arbitrary misrepresentation function whose running time is polynomial in the input size as long as the number of leaves of the underlying tree is bounded by a constant. |
| 61 | On Random Quotas and Proportional Representation in Weighted Voting Games | Yair Zick | In our work, we show that not only does proportional representation hold in expectation, it also holds for many quotas. |
| 62 | Robust Constraint Satisfaction and Local Hidden Variables in Quantum Mechanics | Samson Abramsky, Georg Gottlob, Phokion G. Kolaitis | Motivated by considerations in quantum mechanics, we introduce the class of robust constraint satisfaction problems in which the question is whether every partial assignment of a certain length can be extended to a solution, provided the partial assignment does not violate any of the constraints of the given instance. |
| 63 | Just-in-Time Compilation of Knowledge Bases | Gilles Audemard, Jean-Marie Lagniez, Laurent Simon | We propose a new "Just-in-Time" approach for KC. |
| 64 | Maintaining Alternative Values in Constraint-Based Configuration | Caroline Becker, Hélène Fargier | We propose a propagation algorithm that computes all the alternative domains in a single step. |
| 65 | Breakout Local Search for the Vertex Separator Problem | Una Benlic, Jin-Kao Hao | In this paper, we propose the first heuristic approach for the vertex separator problem (VSP), based on Breakout Local Search (BLS). |
| 66 | Detecting and Exploiting Subproblem Tractability | Christian Bessiere, Clement Carbonnel, Emmanuel Hebrard, George Katsirelos, Toby Walsh | We introduce a method to take advantage of this fact by computing a backdoor to this tractable language. |
| 67 | Constraint Acquisition via Partial Queries | Christian Bessiere, Remi Coletta, Emmanuel Hebrard, George Katsirelos, Nadjib Lazaar, Nina Narodytska, Claude-Guy Quimper, Toby Walsh | We provide an algorithm that, given a negative example, focuses onto a constraint of the target network in a number of queries logarithmic in the size of the example. |
| 68 | On the Complexity of Trick-Taking Card Games | Édouard Bonnet, Florian Jamain, Abdallah Saffidine | We define a general class of perfect information two-player trick-taking card games dealing with arbitrary numbers of hands, suits, and suit lengths. |
| 69 | Comprehensive Score: Towards Efficient Local Search for SAT with Long Clauses | Shaowei Cai, Kaile Su | It is widely acknowledged that stochastic local search (SLS) algorithms can efficiently find models of satisfiable formulae for the Boolean Satisfiability (SAT) problem. |
| 70 | A Tree-Based Tabu Search Algorithm for the Manpower Allocation Problem with Time Windows and Job-Teaming Constraints | Yilin Cai, Zizhen Zhang, Songshan Guo, Hu Qin, Andrew Lim | Consequently, we develop for the problem a novel tabu search algorithm employing search operators based on the tree data structure. |
| 71 | On the Complexity of Global Scheduling Constraints under Structural Restrictions | Geoffrey Chu, Serge Gaspers, Nina Narodytska, Andreas Schutt, Toby Walsh | We investigate the computational complexity of two global constraints, CUMULATIVE and INTERDISTANCE. |
| 72 | Breaking Symmetries in Graph Representation | Michael Codish, Alice Miller, Patrick Prosser, Peter J. Stuckey | In this paper we introduce novel, effective and compact, symmetry breaking constraints for undirected graph search. |
| 73 | Variable Elimination in Binary CSP via Forbidden Patterns | David A. Cohen, Martin C. Cooper, Guillaume Escamocher, Stanislav Živný | We show that there are essentially just four variable elimination rules defined by forbidding generic sub-instances, known as irreducible patterns, in arc-consistent CSP instances. |
| 74 | Weight-Enhanced Diversification in Stochastic Local Search for Satisfiability | Thach-Thao Duong, Duc Nghia Pham, Abdul Sattar, M. A. Hakim Newton | In this paper, we introduce new heuristics to improve the effectiveness of Novelty Walk in terms of reducing search stagnation. |
| 75 | An Approach to Abductive Reasoning in Equational Logic | Mnacho Echenim, Nicolas Peltier, Sophie Tourret | We have devised such a tool in ground flat equational logic, in which literals are equations or disequations between constants. |
| 76 | Dominance Rules for the Choquet Integral in Multiobjective Dynamic Programming | Lucie Galand, Julien Lesca, Patrice Perny | In this paper we focus on the determination of the preferred tradeoffs in the Pareto set where preference is measured by a Choquet integral. |
| 77 | Constraint Satisfaction and Fair Multi-Objective Optimization Problems: Foundations, Complexity, and Islands of Tractability | Gianluigi Greco, Francesco Scarcello | An extension of the CSP optimization framework tailored to identify fair solutions to instances involving multiple optimization functions is studied. |
| 78 | Preserving Partial Solutions while Relaxing Constraint Networks | Éric Grégoire, Jean-Marie Lagniez, Bertrand Mazure | The focus is on two intertwined issues. |
| 79 | Sufficiency-Based Selection Strategy for MCTS | Stefan Freyr Gudmundsson, Yngvi Björnsson | In this paper we investigate a selection strategy for MCTS to alleviate this problem. |
| 80 | DeQED: An Efficient Divide-and-Coordinate Algorithm for DCOP | Daisuke Hatano, Katsutoshi Hirayama | This paper presents a new DCOP algorithm calledDeQED (Decomposition with Quadratic Encoding to Decentralize). |
| 81 | Extending Simple Tabular Reduction with Short Supports | Christopher Jefferson, Peter Nightingale | In this paper we present ShortSTR2, a development of the Simple Tabular Reduction algorithm STR2+. |
| 82 | Monte Carlo *-Minimax Search | Marc Lanctot, Abdallah Saffidine, Joel Veness, Chris Archibald, Mark H. M. Winands | This paper introduces Monte Carlo *-Minimax Search (MCMS), a Monte Carlo search algorithm for turned-based, stochastic, two-player, zero-sum games of perfect information. |
| 83 | Double-Wheel Graphs Are Graceful | Ronan Le Bras, Carla P. Gomes, Bart Selman | We present the first polynomial time construction procedure for generating graceful double-wheel graphs. |
| 84 | Predicting the Size of Depth-First Branch and Bound Search Trees | Levi H. S. Lelis, Lars Otten, Rina Dechter | This paper provides algorithms for predicting the size of the Expanded Search Tree (EST) of Depth-first Branch and Bound algorithms (DFBnB) for optimization tasks. |
| 85 | Target-Value Search Revisited | Carlos Linares López, Roni Stern, Ariel Felner | In this work we develop the theory required to solve this problem optimally for any type of graphs. |
| 86 | Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering | Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann | We devise a new classifier that selects solvers based on a cost-sensitive hierarchical clustering model. |
| 87 | On Computing Minimal Correction Subsets | Joao Marques-Silva, Federico Heras, Mikolas Janota, Alessandro Previti, Anton Belov | More importantly, the paper proposes a novel algorithm for computing MCSes. |
| 88 | Search Strategies for Optimal Multi-Way Number Partitioning | Michael D. Moffitt | In this work, we develop a new optimal algorithm for multi-way number partitioning. |
| 89 | Three Generalizations of the FOCUS Constraint | Nina Narodytska, Thierry Petit, Mohamed Siala, Toby Walsh | To tackle this issue, we propose three generalizations of the FOCUS constraint. |
| 90 | Subset Selection of Search Heuristics | Chris Rayner, Nathan Sturtevant, Michael Bowling | We treat this as an optimization problem, and proceed by translating a natural loss function into a submodular and monotonic utility function under which greedy selection is guaranteed to be near-optimal. |
| 91 | Semiring-Based Mini-Bucket Partitioning Schemes | Emma Rollon, Javier Larrosa, Rina Dechter | In this paper we address the partitioning problem which occurs in many approximation techniques such as mini-bucket elimination and join-graph propagation algorithms. |
| 92 | Improved Bin Completion for Optimal Bin Packing and Number Partitioning | Ethan L. Schreiber, Richard E. Korf | We describe three improvements to BC which result in a speedup of up to five orders of magnitude as compared to the original BC algorithm. |
| 93 | Forward Perimeter Search with Controlled Use of Memory | Thorsten Schütt, Robert Döbbelin, Alexander Reinefeld | We propose Forward Perimeter Search (FPS), a heuristic search with controlled use of memory. |
| 94 | Minimizing Writes in Parallel External Memory Search | Nathan R. Sturtevant, Matthew J. Rutherford | We introduce the Write-Minimizing Breadth-First Search (WMBFS) algorithm which is designed to minimizethe number of writes performed in an external-memory BFS. |
| 95 | Towards Rational Deployment of Multiple Heuristics in A* | David Tolpin, Tal Beja, Solomon Eyal Shimony, Ariel Felner, Erez Karpas | In this paper we aim to reduce the time spent on computing heuristics. |
| 96 | A Unified Approximate Nearest Neighbor Search Scheme by Combining Data Structure and Hashing | Debing Zhang, Genmao Yang, Yao Hu, Zhongming Jin, Deng Cai, Xiaofei He | In this paper, we propose a novel unified approximate nearest neighbor search scheme to combine the advantages of both the effective data structure and the fast Hamming distance computation in hashing methods. |
| 97 | Verifiable Equilibria in Boolean Games | Thomas Ågotnes, Paul Harrenstein, Wiebe van der Hoek, Michael Wooldridge | We formalise and investigate this concept using a model of Boolean games with incomplete information. |
| 98 | Efficient Approach to Solve the Minimal Labeling Problem of Temporal and Spatial Qualitative Constraints | Nouhad Amaneddine, Jean-François Condotta, Michael Sioutis | In this paper, we focus on the minimal labeling problem (MLP) and we propose an algorithm to efficiently derive all the feasible base relations of a QCN. |
| 99 | Exchanging OWL 2 QL Knowledge Bases | Marcelo Arenas, Elena Botoeva, Diego Calvanese, Vladislav Ryzhikov | In this paper, we study this fundamental problem for knowledge bases and mappings expressed in OWL 2 QL, the profile of OWL 2 based on the description logic DL-LiteR. |
| 100 | Temporal Description Logic for Ontology-Based Data Access | Alessandro Artale, Roman Kontchakov, Frank Wolter, Michael Zakharyaschev | Our aim is to investigate ontology-based data access over temporal data with validity time and ontologies capable of temporal conceptual modelling. |
| 101 | Functional Stable Model Semantics and Answer Set Programming Modulo Theories | Michael Bartholomew, Joohyung Lee | We demonstrate that the functional stable model semantics plays an important role in the framework of "Answer Set Programming Modulo Theories (ASPMT)" — a tight integration of answer set programming and satisfiability modulo theories, under which existing integration approaches can be viewed as special cases where the role of functions is limited. |
| 102 | Decidability of Model Checking Non-Uniform Artifact-Centric Quantified Interpreted Systems | Francesco Belardinelli, Alessio Lomuscio | In the present contribution we show that model checking bounded, non-uniform artifact-centric systems is undecidable. |
| 103 | Reasoning about Continuous Uncertainty in the Situation Calculus | Vaishak Belle, Hector J. Levesque | In this paper, we show how this limitation in their approach can be lifted. |
| 104 | Syntactic Computation of Hybrid Possibilistic Conditioning under Uncertain Inputs | Salem Benferhat, Célia da Costa Pereira, Andrea G. B. Tettamanzi | We extend hybrid possibilistic conditioning to deal with inputs consisting of a set of triplets composed of propositional formulas, the level at which the formulas should be accepted, and the way in which their models should be revised. |
| 105 | Automating Quantified Conditional Logics in HOL | Christoph Benzmüller | Automating Quantified Conditional Logics in HOL |
| 106 | First-Order Rewritability of Atomic Queries in Horn Description Logics | Meghyn Bienvenu, Carsten Lutz, Frank Wolter | We study FO-rewritings and their existence for a basic class of queries and for ontologies formulated in Horn DLs such as Horn-SHI and EL. |
| 107 | Conjunctive Regular Path Queries in Lightweight Description Logics | Meghyn Bienvenu, Magdalena Ortiz, Mantas Šimkus | This paper aims to bridge this gap by providing algorithms and tight complexity bounds for answering two-way conjunctive regular path queries over DL knowledge bases formulated in lightweight DLs of the DL-Lite and EL families. |
| 108 | Tractable Queries for Lightweight Description Logics | Meghyn Bienvenu, Magdalena Ortiz, Mantas Šimkus, Guohui Xiao | To obtain a more practical approach, we propose a concrete polynomial-time algorithm for answering acyclic CQs based on rewriting queries into datalog programs. |
| 109 | Tractable Approximations of Consistent Query Answering for Robust Ontology-Based Data Access | Meghyn Bienvenu, Riccardo Rosati | In this paper, we address this problem by proposing two new families of inconsistency-tolerant semantics which approximate the CQA semantics from above and from below and converge to it in the limit. |
| 110 | The Markov Assumption: Formalization and Impact | Alexander Bochman | We provide both a semantic interpretation and logical (inferential) characterization of the Markov principle that underlies the main action theories in AI. |
| 111 | Positive Subsumption in Fuzzy EL with General t-Norms | Stefan Borgwardt, Rafael Peñaloza | We study the reasoning problem of deciding positive subsumption in fuzzy EL with semantics based on general t-norms. |
| 112 | The Impact of Disjunction on Query Answering under Guarded-Based Existential Rules | Pierre Bourhis, Michael Morak, Andreas Pieris | We study the complexity of conjunctive query answering under (weakly-)(frontier-)guarded disjunctive existential rules, i.e., existential rules extended with disjunction, and their main subclasses, linear rules and inclusion dependencies (IDs). |
| 113 | Abstract Dialectical Frameworks Revisited | Gerhard Brewka, Stefan Ellmauthaler, Hannes Strass, Johannes Peter Wallner, Stefan Woltran | We present various new concepts and results related to abstract dialectical frameworks (ADFs), a powerful generalization of Dung’s argumentation frameworks (AFs). |
| 114 | Verification of Inconsistency-Aware Knowledge and Action Bases | Diego Calvanese, Evgeny Kharlamov, Marco Montali, Ario Santoso, Dmitriy Zheleznyakov | We address this problem by showing how inconsistency handling based on the notion of repairs can be integrated into KABs, resorting to inconsistency-tolerant semantics. |
| 115 | Automated Reasoning to Infer All Minimal Keys | P. Cordero, M. Enciso, A. Mora | Wastl introduced for first time a tableaux-like method based on an inference system for deriving all minimal keys from a relational schema. |
| 116 | Do Hard SAT-Related Reasoning Tasks Become Easier in the Krom Fragment? | Nadia Creignou, Reinhard Pichler, Stefan Woltran | In this work, we focus on reasoning tasks in the areas of belief revision and logic-based abduction and show that in some cases the restriction to Krom formulas (i.e., formulas in CNF where clauses have at most two literals) decreases the complexity, while in others it does not. |
| 117 | Computing Datalog Rewritings Beyond Horn Ontologies | Bernardo Cuenca Grau, Boris Motik, Giorgos Stoilos, Ian Horrocks | In this paper, we study the possibilities of answering queries over non-Horn ontologies using datalog rewritings. |
| 118 | Sequences of Mechanisms for Causal Reasoning in Artificial Intelligence | Denver Dash, Mark Voortman, Martijn de Jongh | We present a new approach to token-level causal reasoning that we call Sequences Of Mechanisms (SoMs), which models causality as a dynamic sequence of active mechanisms that chain together to propagate causal influence through time. |
| 119 | Bounded Epistemic Situation Calculus Theories | Giuseppe De Giacomo, Yves Lespérance, Fabio Patrizi | We define the class of e-bounded theories in the epistemic situation calculus, where the number of fluent atoms that the agent thinks may be true is bounded by a constant. |
| 120 | Linear Temporal Logic and Linear Dynamic Logic on Finite Traces | Giuseppe De Giacomo, Moshe Y. Vardi | In this paper we look into the assumption of interpreting LTL over finite traces. |
| 121 | A Formal Account of Nondeterministic and Failed Actions | James P. Delgrande, Hector J. Levesque | In this paper we provide a qualitative theory of nondeterminism. |
| 122 | Data Repair of Inconsistent DL-Programs | Thomas Eiter, Michael Fink, Daria Stepanova | We analyze the complexity of the notion, and we extend an algorithm for evaluating DL-programs to compute repair answer sets, under optional selection of preferred repairs. |
| 123 | Towards a Knowledge Compilation Map for Heterogeneous Representation Languages | Hélène Fargier, Pierre Marquis, Alexandre Niveau | To fill the gap, we present a generalized framework into which comparing formally heterogeneous representation languages becomes feasible. |
| 124 | Semiring Labelled Decision Diagrams, Revisited: Canonicity and Spatial Efficiency Issues | Hélène Fargier, Pierre Marquis, Nicolas Schmidt | In this paper, the SLDD family is revisited. |
| 125 | FQHT: The Logic of Stable Models for Logic Programs with Intensional Functions | Luis Fariñas del Cerro, David Pearce, Agustín Valverde | We provide a logical semantics, a Gentzen style proof theory and establish completeness results. |
| 126 | On the Complexity of Probabilistic Abstract Argumentation | Bettina Fazzinga, Sergio Flesca, Francesco Parisi | In this setting, we address the fundamental problem of computing the probability that a set of arguments is an extension according to a given semantics. |
| 127 | Representation and Reasoning about General Solid Rectangles | Xiaoyu Ge, Jochen Renz | In this paper we develop and analyze a qualitative spatial representation for GSRs. |
| 128 | Advanced Conflict-Driven Disjunctive Answer Set Solving | Martin Gebser, Benjamin Kaufmann, Torsten Schaub | We introduce a new approach to disjunctive ASP solving that aims at an equitable interplay between "generating" and "testing" solver units. |
| 129 | A Strongly-Local Contextual Logic | Michael James Gratton | A Strongly-Local Contextual Logic |
| 130 | Bounded Programs: A New Decidable Class of Logic Programs with Function Symbols | Sergio Greco, Cristian Molinaro, Irina Trubitsyna | To cope with this problem, recent research has focused on identifying classes of logic programs imposing restrictions on the use of function symbols, but guaranteeing decidability of common inference tasks. |
| 131 | Iterated Boolean Games | Julian Gutierrez, Paul Harrenstein, Michael Wooldridge | In order to model the strategies that players use in such games, we use a finite state machine model. |
| 132 | Implicit Learning of Common Sense for Reasoning | Brendan Juba | We propose that this is possible if the learning only occurs implicitly, i.e., without generating an explicit representation. |
| 133 | Knowledge Compilation for Model Counting: Affine Decision Trees | Frédéric Koriche, Jean-Marie Lagniez, Pierre Marquis, Samuel Thomas | In order to fill the gap, we introduce the language EADT of (extended) affine decision trees. |
| 134 | Parameterized Complexity of Optimal Planning: A Detailed Map | Martin Kronegger, Andreas Pfandler, Reinhard Pichler | The goal of this paper is a systematic parameterized complexity analysis of different variants of propositional STRIPS planning. |
| 135 | Syntactic Labelled Tableaux for Łukasiewicz Fuzzy ALC | Agnieszka Kułacka, Dirk Pattinson, Lutz Schröder | Here, we present a decision method that stays closer to logical syntax, a labelled tableau algorithm for Lukasiewicz Fuzzy ALC that calls only on (pure) linear programming, and this only to decide atomic clashes. |
| 136 | Decidable Reasoning in a Logic of Limited Belief with Introspection and Unknown Individuals | Gerhard Lakemeyer, Hector J. Levesque | In this paper, we show how both shortcomings can be overcome by suitably extending the language and its semantics. |
| 137 | StarVars—Effective Reasoning about Relative Directions | Jae Hee Lee, Jochen Renz, Diedrich Wolter | In this paper we present a novel qualitative representation, StarVars, that can solve these problems. |
| 138 | Action Language BC: Preliminary Report | Joohyung Lee, Vladimir Lifschitz, Fangkai Yang | This paper defines a new action description language, called BC, that combines the attractive features of B and C. Examples of formalizing commonsense domains discussed in the paper illustrate the expressive capabilities of BC and the use of answer set solvers for the automation of reasoning about actions described in this language. |
| 139 | Answer Set Programming Modulo Theories and Reasoning about Continuous Changes | Joohyung Lee, Yunsong Meng | Answer Set Programming Modulo Theories (ASPMT) is a new framework of tight integration of answer set programming (ASP) and satisfiability modulo theories (SMT). |
| 140 | Reasoning about State Constraints in the Situation Calculus | Naiqi Li, Yi Fan, Yongmei Liu | In this paper, we propose a sound but incomplete method for automatic verification and discovery of state constraints for a class of action theories that include many planning benchmarks. |
| 141 | Analogico-Deductive Generation of Gödel’s First Incompleteness Theorem from the Liar Paradox | John Licato, Naveen Sundar Govindarajulu, Selmer Bringsjord, Michael Pomeranz, Logan Gittelson | In this paper, we summarize engineering that entails an affirmative answer to this question. |
| 142 | An Epistemic Halpern–Shoham Logic | Alessio R. Lomuscio, Jakub Michaliszyn | We define a family of epistemic extensions of Halpern-Shoham logic for reasoning about temporal-epistemic properties of multi-agent systems. |
| 143 | Preference-Based Query Answering in Datalog+/– Ontologies | Thomas Lukasiewicz, Maria Vanina Martinez, Gerardo I. Simari | In this paper, we propose the first (to our knowledge) integration of ontology languages with preferences as in relational databases by developing PrefDatalog+/-, an extension of the Datalog+/- family of languages with preference management formalisms closely related to those previously studied for relational databases. |
| 144 | Ontology-Based Data Access with Closed Predicates Is Inherently Intractable (Sometimes) | Carsten Lutz, Inanç Seylan, Frank Wolter | We analyze this situation on the level of individual ontologies formulated in the description logics DL-Lite and EL and show that in all cases where answering CQs with (open and) closed predicates is tractable, it coincides with answering CQs with all predicates assumed open. |
| 145 | Computing Stable Models for Nonmonotonic Existential Rules | Despoina Magka, Markus Krötzsch, Ian Horrocks | In this work, we consider function-free existential rules extended with nonmonotonic negation under a stable model semantics. |
| 146 | The Route to Success – A Performance Comparison of Diagnosis Algorithms | Iulia Nica, Ingo Pill, Thomas Quaritsch, Franz Wotawa | In this paper we contribute to answering this question. |
| 147 | Backdoors to Abduction | Andreas Pfandler, Stefan Rümmele, Stefan Szeider | In this work we use structural properties of the Abduction instance to break this complexity barrier. |
| 148 | Behavioral Diagnosis of LTL Specifications at Operator Level | Ingo Pill, Thomas Quaritsch | Drawing on efficient SAT encodings, we show in this paper how to achieve that effectively for specifications in LTL. |
| 149 | Cyclic Causal Models with Discrete Variables: Markov Chain Equilibrium Semantics and Sample Ordering | David Poole, Mark Crowley | We analyze the foundations of cyclic causal models for discrete variables, and compare structural equation models (SEMs) to an alternative semantics as the equilibrium (stationary) distribution of a Markov chain. |
| 150 | Learning from Polyhedral Sets | Salvatore Ruggieri | In this paper, we investigate the problem of learning a parameterized linear system whose class of polyhedra includes a given set of example polyhedral sets and it is minimal. |
| 151 | Efficient Extraction and Representation of Spatial Information from Video Data | Hajar Sadeghi Sokeh, Stephen Gould, Jochen Renz | We present efficient algorithms both for extracting and storing spatial information from video, as well as for processing this information in order to obtain useful spatial features. |
| 152 | Combining RCC5 Relations with Betweenness Information | Steven Schockaert, Sanjiang Li | To further the role of RCC5 as a vehicle for conceptual reasoning, in this paper we combine RCC5 relations with information about betweenness of regions. |
| 153 | Interpolative Reasoning with Default Rules | Steven Schockaert, Henri Prade | In this paper, we introduce an inference system for interpolating default rules, based on a geometric semantics in which normality is related to spatial density and interpolation is related to geometric betweenness. |
| 154 | On Condensing a Sequence of Updates in Answer-Set Programming | Martin Slota, João Leite | In this paper we solve the state condensing problem for two foundational rule update semantics, using nested logic programs. |
| 155 | Nominal Schema Absorption | Andreas Steigmiller, Birte Glimm, Thorsten Liebig | We address this by extending the well-known optimisation of absorption as well as the standard tableau calculus to directly handle the (absorbed) nominal schema axioms. |
| 156 | Granular Description of Qualitative Change | John G. Stell | We present a novel framework for the qualitative description of spatial regions based on two levels of granularity. |
| 157 | A Rational Extension of Stable Model Semantics to the Full Propositional Language | Shahab Tasharrofi | Stable model semantics, as the semantics behind this success, has been subject to many extensions. |
| 158 | Compact Rewritings for Existential Rules | Michaël Thomazo | In this paper, we consider ontologies described by existential rules (also known as Datalog+/-), a framework that generalizes lightweight description logics. |
| 159 | A Classification of First-Order Progressable Action Theories in Situation Calculus | Stavros Vassos, Fabio Patrizi | In this paper we focus on a recent result about the decidability of projection and use it to drive results for the problem of progression. |
| 160 | An Alternative Axiomatization of DEL and Its Applications | Yanjing Wang, Guillaume Aucher | In this paper, we provide a new axiomatization of the event-model-based Dynamic Epistemic Logic, based on the completeness proof method proposed in [Wang and Cao, 2013]. |
| 161 | Knowing That, Knowing What, and Public Communication: Public Announcement Logic with Kv Operators | Yanjing Wang, Jie Fan | In the same paper, Plaza also introduced an interesting "know-value" operator Kv and listed a few valid formulas of PAL+Kv. However, it is unknown that whether these formulas, on top of the axioms for PAL, completely axiomatize PAL+Kv. |
| 162 | Multi-Agent Subset Space Logic | Yì N. Wáng, Thomas Ågotnes | In this paper we argue that the few existing attempts at multi-agent versions of SSL are unsatisfactory, and propose a new multi-agent subset space logic which is a natural extension of single-agent SSL. |
| 163 | Forgetting for Answer Set Programs Revisited | Yisong Wang, Kewen Wang, Mingyi Zhang | Forgetting for Answer Set Programs Revisited |
| 164 | Transition Constraints: A Study on the Computational Complexity of Qualitative Change | Matthias Westphal, Julien Hué, Stefan Wölfl, Bernhard Nebel | This paper presents a study on the computational complexity of qualitative change. |
| 165 | Supremal Realizability of Behaviors with Uncontrollable Exogenous Events | Nitin Yadav, Paolo Felli, Giuseppe De Giacomo, Sebastian Sardina | In this paper we answer positively, by showing that there exists a unique supremal realizable target behavior satisfying the specification. |
| 166 | Multi-Agent Epistemic Explanatory Diagnosis via Reasoning about Actions | Quan Yu, Ximing Wen, Yongmei Liu | The task of explanatory diagnosis conjectures actions to explain observations.This is a common task in real life and an essential ability of intelligent agents.It becomes more complicated in multi-agent scenarios, since agents’ actions may be partially observable to other agents, and observations might involve agents’ knowledge about the world or other agents’ knowledge or even common knowledge of a group of agents.For example, we might want to explain the observation that p does not hold,but Ann believes p, or the observation that Ann, Bob, and Carl commonly believe p. In this paper, we formalize the multi-agent explanatory diagnosis task in the framework of dynamic epistemic logic, where Kripke models of actions are used to represent agents’ partial observability of actions. |
| 167 | Most Specific Generalizations w.r.t. General EL-TBoxes | Benjamin Zarrieß, Anni-Yasmin Turhan | This paper provides necessary and sufficient conditions for the existence of these two kinds of concepts. |
| 168 | First-Order Expressibility and Boundedness of Disjunctive Logic Programs | Heng Zhang, Yan Zhang | In this paper, the fixed point semantics developed in [Lobo et al., 1992] is generalized to disjunctive logic programs with default negation and over arbitrary structures, and proved to coincide with the stable model semantics. |
| 169 | Definability of Horn Revision from Horn Contraction | Zhiqiang Zhuang, Maurice Pagnucco, Yan Zhang | In this paper, we address this problem by obtaining a model-based Horn revision through the model-based Horn contraction studied in [Zhuang and Pagnucco, 2012]. |
| 170 | Learning Community-Based Preferences via Dirichlet Process Mixtures of Gaussian Processes | Ehsan Abbasnejad, Scott Sanner, Edwin V. Bonilla, Pascal Poupart | We evaluate our approach on a variety of preference data sources including Amazon Mechanical Turk showing that our method is more scalable and as accurate as previous GP-based preference learning work. |
| 171 | An Ensemble of Bayesian Networks for Multilabel Classification | Antonucci Alessandro, Giorgio Corani, Denis Mauá, Sandra Gabaglio | We present a novel approach for multilabel classification based on an ensemble of Bayesian networks. |
| 172 | Self-Organized Neural Learning of Statistical Inference from High-Dimensional Data | Johannes Bauer, Stefan Wermter | In this paper, we address the question of how the brain might solve this problem: We present an unsupervised artificial neural network algorithm which takes from the self-organizing map (SOM) algorithm the ability to learn a latent variable model from its input. |
| 173 | Basic Level in Formal Concept Analysis: Interesting Concepts and Psychological Ramifications | Radim Belohlavek, Martin Trnecka | We present a study regarding basic level of concepts in conceptual categorization. |
| 174 | Exact Top-k Feature Selection via l2,0-Norm Constraint | Xiao Cai, Feiping Nie, Heng Huang | In this paper, we propose a novel robust and pragmatic feature selection approach. |
| 175 | Regularized Latent Least Square Regression for Cross Pose Face Recognition | Xinyuan Cai, Chunheng Wang, Baihua Xiao, Xue Chen, Ji Zhou | In this paper, we propose a novel cross-pose face recognition method named as Regularized Latent Least Square Regression (RLLSR). |
| 176 | Robust Tensor Clustering with Non-Greedy Maximization | Xiaochun Cao, Xingxing Wei, Yahong Han, Yi Yang, Dongdai Lin | In this paper, we propose an algorithm of Robust Tensor Clustering (RTC). |
| 177 | Central Clustering of Categorical Data with Automated Feature Weighting | Lifei Chen, Shengrui Wang | In this paper, we propose a novel kernel-density-based definition using a Bayes-type probability estimator. |
| 178 | Dimensionality Reduction with Generalized Linear Models | Mo Chen, Wei Li, Wei Zhang, Xiaogang Wang | In this paper, we propose a general dimensionality reduction method for data generated from a very broad family of distributions and nonlinear functions based on the generalized linear model, called Generalized Linear Principal Component Analysis (GLPCA). |
| 179 | Generalized Relational Topic Models with Data Augmentation | Ning Chen, Jun Zhu, Fei Xia, Bo Zhang | This paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference with a regularization parameter to deal with the imbalanced link structure issue in common real networks; and 3) instead of doing variational approximation with strict mean-field assumptions, we present a collapsed Gibbs sampling algorithm for the generalized relational topic models without making restricting assumptions. |
| 180 | Domain Adaptation with Topical Correspondence Learning | Zheng Chen, Weixiong Zhang | We develop a novel domain adaptation method for text document classification under the framework of Non-negative Matrix Factorization. |
| 181 | Bayesian Nonparametric Feature Construction for Inverse Reinforcement Learning | Jaedeug Choi, Kee-Eung Kim | We propose a Bayesian nonparametric approach to identifying useful composite features for learning the reward function. |
| 182 | A Lossy Counting Based Approach for Learning on Streams of Graphs on a Budget | Giovanni Da San Martino, Nicolò Navarin, Alessandro Sperduti | In this paper we present a novel approach inspired by the Passive Aggressive and the Lossy Counting algorithms. |
| 183 | Bootstrap Learning via Modular Concept Discovery | Eyal Dechter, Jon Malmaud, Ryan P. Adams Joshua B. Tenenbaum | We propose an iterative procedure for exploring such spaces: in the first step of each iteration, the learner explores a finite subset of the domain, guided by a stochastic grammar; in the second step, the learner compresses the successful solutions from the first step to estimate a new stochastic grammar. |
| 184 | Topic Extraction from Online Reviews for Classification and Recommendation | Ruihai Dong, Markus Schaal, Michael P. O’Mahony, Barry Smyth | In this paper, we describe and evaluate techniques for identifying and recommending helpful product reviews using a combination of review features, including topical and sentiment information, mined from a review corpus. |
| 185 | Towards Robust Co-Clustering | Liang Du, Yi-Dong Shen | In this paper, we extend GNMTF by introducing a sparse outlier matrix into the data reconstruction function and applying the l1 norm to measure graph dual regularization errors, which leads to a novel Robust Co-Clustering (RCC) method. |
| 186 | Learning Finite Beta-Liouville Mixture Models via Variational Bayes for Proportional Data Clustering | Wentao Fan, Nizar Bouguila | In contrast to the conventional expectation maximization (EM) algorithm, commonly used for learning finite mixture models, the proposed algorithm has the advantages that it is more efficient from a computational point of view and by preventing over- and under-fitting problems. |
| 187 | Optimizing Cepstral Features for Audio Classification | Zhouyu Fu, Guojun Lu, Kai Ming Ting, Dengsheng Zhang | In this paper, we present a novel approach for learning optimized cepstral features directly from audio data to better discriminate between different categories of signals in classification tasks. |
| 188 | Uniform Convergence, Stability and Learnability for Ranking Problems | Wei Gao, Zhi-Hua Zhou | In this paper, we study the relation between uniform convergence, stability and learnability of ranking. |
| 189 | Active Learning for Level Set Estimation | Alkis Gotovos, Nathalie Casati, Gregory Hitz, Andreas Krause | We propose LSE, an algorithm that guides both sampling and classification based on GP-derived confidence bounds, and provide theoretical guarantees about its sample complexity. |
| 190 | Histogram of Oriented Displacements (HOD): Describing Trajectories of Human Joints for Action Recognition | Mohammad A. Gowayyed, Marwan Torki, Mohamed E. Hussein, Motaz El-Saban | Here, we propose a novel descriptor for 2D trajectories: Histogram of Oriented Displacements (HOD). |
| 191 | Multi-Prototype Label Ranking with Novel Pairwise-to-Total-Rank Aggregation | Mihajlo Grbovic, Nemanja Djuric, Slobodan Vucetic | We propose a multi-prototype-based algorithm for online learning of soft pairwise-preferences over labels. |
| 192 | MiningZinc: A Modeling Language for Constraint-based Mining | Tias Guns, Anton Dries, Guido Tack, Siegfried Nijssen, Luc De Raedt | We introduce MiningZinc, a general framework for constraint-based pattern mining, one of the most popular tasks in data mining. |
| 193 | Probabilistic Multi-Label Classification with Sparse Feature Learning | Yuhong Guo, Wei Xue | In this paper we propose a probabilistic multi-label classification model based on novel sparse feature learning. |
| 194 | Co-Regularized Ensemble for Feature Selection | Yahong Han, Yi Yang, Xiaofang Zhou | In this paper, we add a joint l2,1-norm on multiple feature selection matrices to ensemble different classifiers’ loss function into a joint optimization framework. |
| 195 | Improving Traffic Prediction with Tweet Semantics | Jingrui He, Wei Shen, Phani Divakaruni, Laura Wynter, Rick Lawrence | To address this problem, in this paper, for the first time, we examine whether it is possible to use the rich information in online social media to improve longer-term traffic prediction. |
| 196 | A General Framework for Interacting Bayes-Optimally with Self-Interested Agents Using Arbitrary Parametric Model and Model Prior | Trong Nghia Hoang, Kian Hsiang Low | To overcome these practical limitations of FDM, we propose a generalization of BRL to integrate the general class of parametric models and model priors, thus allowing practitioners’ domain knowledge to be exploited to produce a fine-grained and compact representation of the other agent’s behavior. |
| 197 | What Users Care About: A Framework for Social Content Alignment | Lei Hou, Juanzi Li, Xiaoli Li, Jiangfeng Qu, Xiaofei Guo, Ou Hui, Jie Tang | In this paper, we propose a novel framework that is able to automatically detect the subtopics from a given Web document, and also align the associated social comments with the detected subtopics. |
| 198 | Efficient Kernel Learning from Side Information Using ADMM | En-Liang Hu, James T. Kwok | In this paper, we propose a novel solver based on the alternating direction method of multipliers (ADMM). |
| 199 | Active Learning via Neighborhood Reconstruction | Yao Hu, Debing Zhang, Zhongming Jin, Deng Cai, Xiaofei He | In this paper, we propose a novel framework named Active Learning via Neighborhood Reconstruction (ALNR) by taking into account the locality information directly during the selection. |
| 200 | Online Hashing | Long-Kai Huang, Qiang Yang, Wei-Shi Zheng | In this paper, we address the problem by developing an online hashing learning algorithm to get hashing model accommodate to each new pair of data. |
| 201 | Discovering Different Types of Topics: Factored Topic Models | Yun Jiang, Ashutosh Saxena | In this paper, our goal is to discover such different types of topics, if they exist. |
| 202 | Prior-Free Exploration Bonus for and beyond Near Bayes-Optimal Behavior | Kenji Kawaguchi, Hiroshi Sato | As full Bayesian planning is intractable except for special cases, previous work has proposed several approximation methods. |
| 203 | Causal Inference with Rare Events in Large-Scale Time-Series Data | Samantha Kleinberg | Instead, we develop a new approach to finding the causal impact of rare events that leverages the large amount of data available to infer a model of a system’s functioning and evaluates how rare events explain deviations from usual behavior. |
| 204 | Active Learning for Teaching a Robot Grounded Relational Symbols | Johannes Kulick, Marc Toussaint, Tobias Lang, Manuel Lopes | In this paper we formalize human-robot teaching of grounded symbols as an active learning problem, where the robot actively generates pick-and-place geometric situations that maximize its information gain about the symbol to be learned. |
| 205 | Adaptive Thresholding in Structure Learning of a Bayesian Network | Boaz Lerner, Michal Afek, Rafi Bojmel | We analyze the impact on mutual information – a CI measure – of factors, such as sample size, degree of variable dependence, and variables’ cardinalities. |
| 206 | A Bayesian Factorised Covariance Model for Image Analysis | Jun Li, Dacheng Tao | This paper presents a specialised Bayesian model for analysing the covariance of data that are observed in the form of matrices, which is particularly suitable for images. |
| 207 | Low-Rank Coding with b-Matching Constraint for Semi-Supervised Classification | Sheng Li, Yun Fu | In this paper, we develop a novel approach to constructing graph, which is based on low-rank coding and $b$-matching constraint. |
| 208 | Active Learning with Multi-Label SVM Classification | Xin Li, Yuhong Guo | Though active learning has been widely studied on reducing labeling effort for single-label problems, current research on multi-label active learning remains in a preliminary state. |
| 209 | Large-Scale Spectral Clustering on Graphs | Jialu Liu, Chi Wang, Marina Danilevsky, Jiawei Han | In this paper we propose an efficient clustering algorithm for large-scale graph data using spectral methods. |
| 210 | Learning Discriminative Representations from RGB-D Video Data | Li Liu, Ling Shao | In this paper, we introduce an adaptive learning methodology to automatically extract (holistic) spatio-temporal features, simultaneously fusing the RGB and depth information, from RGBD video data for visual recognition tasks. The proposed method is systematically evaluated on a new hand gesture dataset, SKIG, that we collected ourselves and the public MSRDailyActivity3D dataset, respectively. |
| 211 | Online Expectation Maximization for Reinforcement Learning in POMDPs | Miao Liu, Xuejun Liao, Lawrence Carin | We present online nested expectation maximization for model-free reinforcement learning in a POMDP. |
| 212 | The Multi-Feature Information Bottleneck with Application to Unsupervised Image Categorization | Zhengzheng Lou, Yangdong Ye, Xiaoqiang Yan | We present a novel unsupervised data analysis method, Multi-feature Information Bottleneck (MfIB), which is an extension of the Information Bottleneck (IB). |
| 213 | Learning Canonical Correlations of Paired Tensor Sets Via Tensor-to-Vector Projection | Haiping Lu | For paired tensor data sets, we propose a multilinear CCA (MCCA) method. |
| 214 | Learning Descriptive Visual Representation by Semantic Regularized Matrix Factorization | Zhiwu Lu, Yuxin Peng | This paper presents a novel semantic regularized matrix factorization method for learning descriptive visual bag-of-words (BOW) representation. |
| 215 | Thinking of Images as What They Are: Compound Matrix Regression for Image Classification | Zhigang Ma, Yi Yang, Feiping Nie, Nicu Sebe | In this paper, we propose a new classification framework for image matrices. |
| 216 | An Empirical Investigation of Ceteris Paribus Learnability | Loizos Michael, Elena Papageorgiou | This work presents the first empirical investigation of an algorithm for reliably and efficiently learning CP-nets in a manner that is minimally intrusive. |
| 217 | Statistical Tests for the Detection of the Arrow of Time in Vector Autoregressive Models | Pablo Morales-Mombiela, Daniel Hernández-Lobato, Alberto Suárez | The problem of detecting the direction of time in vector Autoregressive (VAR) processes using statistical techniques is considered. |
| 218 | Meta-Interpretive Learning of Higher-Order Dyadic Datalog: Predicate Invention Revisited | Stephen Muggleton, Dianhuan Lin | In this paper we generalise the approach of Meta-Interpretive Learning (MIL) to that of learning higher-order dyadic datalog programs. |
| 219 | Multi-Modal Image Annotation with Multi-Instance Multi-Label LDA | Cam-Tu Nguyen, De-Chuan Zhan, Zhi-Hua Zhou | We propose Multi-modal Multi-instance Multi-label Latent Dirichlet Allocation (M3LDA), where the model consists of a visual-label part, a textual-label part and a label-topic part. |
| 220 | Adaptive Loss Minimization for Semi-Supervised Elastic Embedding | Feiping Nie, Hua Wang, Heng Huang, Chris Ding | Motivated by this deficiency, we relax the rigid linear embedding constraint and propose to use an elastic embedding constraint on the predicted label matrix such that the manifold structure can be better explored. |
| 221 | Early Active Learning via Robust Representation and Structured Sparsity | Feiping Nie, Hua Wang, Heng Huang, Chris Ding | In this paper, we propose a novel robust active learning method to handle the early stage experimental design problem and select the most representative data points. |
| 222 | Annealed Importance Sampling for Structure Learning in Bayesian Networks | Teppo Niinimäki, Mikko Koivisto | We present a new sampling approach to Bayesian learning of the Bayesian network structure. |
| 223 | Graph Classification with Imbalanced Class Distributions and Noise | Shirui Pan, Xingquan Zhu | In this paper, we propose an imbalanced graph boosting algorithm, igBoost, that progressively selects informative subgraph patterns from imbalanced graph data for learning. |
| 224 | Hierarchical Bayesian Matrix Factorization with Side Information | Sunho Park, Yong-Deok Kim, Seungjin Choi | In this paper we present a method for Bayesian matrix factorization with side information, to handle cold-start problems. |
| 225 | A Scalable Approach to Column-Based Low-Rank Matrix Approximation | Yifan Pi, Haoruo Peng, Shuchang Zhou, Zhihua Zhang | In this paper, we address the column-based low-rank matrix approximation problem using a novel parallel approach. |
| 226 | Multiple Task Learning Using Iteratively Reweighted Least Square | Jian Pu, Yu-Gang Jiang, Jun Wang, Xiangyang Xue | In this paper, we adopt a more general formulation for MTL without making specific structure assumptions. |
| 227 | Active Learning from Relative Queries | Buyue Qian, Xiang Wang, Fei Wang, Hongfei Li, Jieping Ye, Ian Davidson | In this paper, we focus on designing easier questions that can be answered by a non-expert. |
| 228 | Robust Unsupervised Feature Selection | Mingjie Qian, Chengxiang Zhai | A new unsupervised feature selection method, i.e., Robust Unsupervised Feature Selection (RUFS), is proposed. |
| 229 | Path Integral Control by Reproducing Kernel Hilbert Space Embedding | Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar | We present an embedding of stochastic optimal control problems, of the so called path integral form, into reproducing kernel Hilbert spaces. |
| 230 | Machine-Learning-Based Circuit Synthesis | Lior Rokach, Meir Kalech, Gregory Provan, Alexander Feldman | To solve this problem we propose an algorithm, called Circuit-Decomposition Engine (CDE), that is based on learning decision trees, and uses a greedy approach for function learning. |
| 231 | Weighted Path as a Condensed Pattern in a Single Attributed DAG | Jérémy Sanhes, Frédéric Flouvat, Nazha Selmaoui-Folcher, Claude Pasquier, Jean-François Boulicaut | In this paper, we study a new pattern domain for supporting their analysis. |
| 232 | Multi-Dimensional Causal Discovery | Ulrich Schaechtle, Kostas Stathis, Stefano Bromuri | We propose a method for learning causal relations within high-dimensional tensor data as they are typically recorded in non-experimental databases. |
| 233 | Better Generalization with Forecasts | Tom Schaul, Mark Ring | Predictive methods are becoming increasingly popular for representing world knowledge in autonomous agents.A recently introduced predictive method that shows particular promise is the General Value Function (GVF), which is more flexible than previous predictive methods and can more readily capture regularities in the agent’s sensorimotor stream.The goal of the current paper is to investigate the ability of these GVFs (also called "forecasts") to capture such regularities.We generate focused sets of forecasts and measure their capacity for generalization.We then compare the results with a closely related predictive method (PSRs) already shown to have good generalization abilities.Our results indicate that forecasts provide a substantial improvement in generalization, producing features that lead to better value-function approximation (when computed with linear function approximators) than PSRs and better generalization to as-yet-unseen parts of the state space. |
| 234 | Supervised Hypothesis Discovery Using Syllogistic Patterns in the Biomedical Literature | Kazuhiro Seki, Kuniaki Uehara | This paper reports our approach to this problem taking advantage of a triangular chain of relations extracted from published knowledge. |
| 235 | Guarantees of Augmented Trace Norm Models in Tensor Recovery | Ziqiang Shi, Jiqing Han, Tieran Zheng, Ji Li | This paper studies the recovery guarantees of the models of minimizing ||X||∗ + 1/2a ||X||2F where X is a tensor and ||X||∗ and ||X||F are the trace and Frobenius norm of respectively. |
| 236 | Hartigan’s K-Means Versus Lloyd’s K-Means — Is It Time for a Change? | Noam Slonim, Ehud Aharoni, Koby Crammer | Specifically, we characterize a range of problems with various noise levels of the inputs, for which any random partition represents a local minimum for Lloyd’s algorithm, while Hartigan’s algorithm easily converges to the correct solution. |
| 237 | One-Class Conditional Random Fields for Sequential Anomaly Detection | Yale Song, Zhen Wen, Ching-Yung Lin, Randall Davis | We present One-Class Conditional Random Fields (OCCRF) for sequential anomaly detection that learn from a one-class dataset and capture the temporal dependence structure, in an unsupervised fashion. |
| 238 | Measuring Statistical Dependence via the Mutual Information Dimension | Mahito Sugiyama, Karsten M. Borgwardt | We propose to measure statistical dependence between two random variables by the mutual information dimension (MID), and present a scalable parameter-free estimation method for this task. |
| 239 | Unlearning from Demonstration | Keith Sullivan, Ahmed ElMolla, Bill Squires, Sean Luke | We present a set of algorithms which use this corrective data to identify and remove noisy examples in datasets which caused errant classifications, and ultimately errant behavior. |
| 240 | Multi-View Maximum Entropy Discrimination | Shiliang Sun, Guoqing Chao | In this paper, we present a multi-view maximum entropy discrimination framework that is an extension of MED to the scenario of learning with multiple feature sets. |
| 241 | Non-Negative Multiple Matrix Factorization | Koh Takeuchi, Katsuhiko Ishiguro, Akisato Kimura, Hiroshi Sawada | In this paper, we propose a novel matrix factorization method called Non-negative Multiple Matrix Factorization (NMMF), which utilizes complementary data as auxiliary matrices that share the row or column indices of the target matrix. |
| 242 | Linear Bayesian Reinforcement Learning | Nikolaos Tziortziotis, Christos Dimitrakakis, Konstantinos Blekas | This paper proposes a simple linear Bayesian approach to reinforcement learning. |
| 243 | Multi Class Learning with Individual Sparsity | Ben Zion Vatashsky, Koby Crammer | We propose to use other regularizations that promote this type of sparsity, analyze the generalization property of such formulations, and show empirically that indeed, these regularizations not only perform well, but also promote such sparsity structure. |
| 244 | Coupled Attribute Analysis on Numerical Data | Can Wang, Zhong She, Longbing Cao | This paper proposes a framework of the coupled attribute analysis to capture the global dependency of continuous attributes. |
| 245 | Manifold Alignment Preserving Global Geometry | Chang Wang, Sridhar Mahadevan | This paper proposes a novel algorithm for manifold alignment preserving global geometry. |
| 246 | Large Scale Online Kernel Classification | Jialei Wang, Steven C. H. Hoi, Peilin Zhao, Jinfeng Zhuang, Zhi-yong Liu | In this work, we present a new framework for large scale online kernel classification, making kernel methods efficient and scalable for large-scale online learning tasks. |
| 247 | Online Group Feature Selection | Jing Wang, Zhong-Qiu Zhao, Xuegang Hu, Yiu-ming Cheung, Meng Wang, Xindong Wu | Motivated by this, we formulate the online group feature selection problem, and propose a novel selection approach for this problem. |
| 248 | Nonconvex Relaxation Approaches to Robust Matrix Recovery | Shusen Wang, Dehua Liu, Zhihua Zhang | Motivated by the recent developments of nonconvex penalties in sparsity modeling, we propose a nonconvex optimization model for handing the low-rank matrix recovery problem. |
| 249 | A KNN Based Kalman Filter Gaussian Process Regression | Yali Wang, Brahim Chaib-draa | In this paper, we address these challenging data properties by designing a novel K nearest neighbor based Kalman filter Gaussian process (KNN-KFGP) regression. |
| 250 | Bayesian Optimization in High Dimensions via Random Embeddings | Ziyu Wang, Masrour Zoghi, Frank Hutter, David Matheson, Nando de Freitas | In this paper, we introduce a novel random embedding idea to attack this problem. |
| 251 | Deep Feature Learning Using Target Priors with Applications in ECoG Signal Decoding for BCI | Zuoguan Wang, Siwei Lyu, Gerwin Schalk, Qiang Ji | In this work, we describe a new learning method that combines deep feature learning on mixed labeled and unlabeled data sets. |
| 252 | Euler Clustering | Jian-Sheng Wu, Wei-Shi Zheng, Jian-Huang Lai | In this paper, we introduce an Euler clustering, which can not only maintain the benefit of nonlinear modeling using kernel function but also significantly solve the large scale computational problem in kernel-based clustering. |
| 253 | A Theoretic Framework of K-Means-Based Consensus Clustering | Junjie Wu, Hongfu Liu, Hui Xiong, Jie Cao | In this paper, we provide a systematic study on the framework of K-means-based Consensus Clustering (KCC). |
| 254 | Multi-Modal Distance Metric Learning | Pengtao Xie, Eric P. Xing | In this paper, we propose an effective and scalable multi-modal distance metric learning framework. |
| 255 | A Probabilistic Approach to Latent Cluster Analysis | Zhipeng Xie, Rui Dong, Zhengheng Deng, Zhenying He, Weidong Yang | In this paper, we propose a novel cluster ensemble method from probabilistic perspective. |
| 256 | Harmonious Hashing | Bin Xu, Jiajun Bu, Yue Lin, Chun Chen, Xiaofei He, Deng Cai | Harmonious Hashing |
| 257 | Change-Point Detection with Feature Selection in High-Dimensional Time-Series Data | Makoto Yamada, Akisato Kimura, Futoshi Naya, Hiroshi Sawada | Based on this framework, we propose a detection measure called the additive Hilbert-Schmidt Independence Criterion (aHSIC), which is defined as the weighted sum of the HSIC scores between features and its corresponding binary labels. |
| 258 | On Robust Estimation of High Dimensional Generalized Linear Models | Eunho Yang, Ambuj Tewari, Pradeep Ravikumar | We study robust high-dimensional estimation of generalized linear models (GLMs); where a small number k of the n observations can be arbitrarily corrupted, and where the true parameter is high dimensional in the "p > n" regime, but only has a small number s of non-zero entries. |
| 259 | Reduced Heteroscedasticity Linear Regression for Nyström Approximation | Hao Yang, Jianxin Wu | In this paper, we present a novel point of view for the Nyström approximation. |
| 260 | Multi-View Discriminant Transfer Learning | Pei Yang, Wei Gao | We study to incorporate multiple views of data in a perceptive transfer learning framework and propose a Multi-view Discriminant Transfer (MDT) learning approach for domain adaptation. |
| 261 | Smart Hashing Update for Fast Response | Qiang Yang, Long-Kai Huang, Wei-Shi Zheng, Yingbiao Ling | In this paper, we consider updating a hashing model upon gradually increased labelled data in a fast response to users, called smart hashing update (SHU). |
| 262 | Multi-Instance Multi-Label Learning with Weak Label | Shu-Jun Yang, Yuan Jiang, Zhi-Hua Zhou | In this paper, we propose the MIMLwel approach which works by assuming that highly relevant labels share some common instances, and the underlying class means of bags for each label are with a large margin. |
| 263 | Protein Function Prediction by Integrating Multiple Kernels | Guoxian Yu, Huzefa Rangwala, Carlotta Domeniconi, Guoji Zhang, Zili Zhang | In this paper, we propose a method called Protein Function Prediction by Integrating Multiple Kernels(ProMK). |
| 264 | Learning Domain Differences Automatically for Dependency Parsing Adaptation | Mo Yu, Tiejun Zhao, Yalong Bai | In this paper, we address the relation between domain differences and domain adaptation for dependency parsing. |
| 265 | Bilevel Visual Words Coding for Image Classification | Jiemi Zhang, Chenxia Wu, Deng Cai, Jianke Zhu | In this paper, we propose a bilevel visual words coding approach in consideration of representation ability, discriminative power and efficiency. |
| 266 | Sparse Reconstruction for Weakly Supervised Semantic Segmentation | Ke Zhang, Wei Zhang, Yingbin Zheng, Xiangyang Xue | We propose a novel approach to semantic segmentation using weakly supervised labels. |
| 267 | Semi-Supervised Learning with Manifold Fitted Graphs | Tongtao Zhang, Rongrong Ji, Wei Liu, Dacheng Tao, Gang Hua | In this paper, we propose a locality-constrained and sparsity-encouraged manifold fitting approach, aiming at capturing the locally sparse manifold structure into neighborhood graph construction by exploiting a principled optimization model. |
| 268 | Online Community Detection for Large Complex Networks | Wangsheng Zhang, Gang Pan, Zhaohui Wu, Shijian Li | In this paper, we propose an online community detection method for large complex networks, which make it possible to process networks edge-by-edge in a serial fashion. |
| 269 | Multi-View Embedding Learning for Incompletely Labeled Data | Wei Zhang, Ke Zhang, Pan Gu, Xiangyang Xue | We propose a novel method to seek compact embedding that allows efficient retrieval with incompletely-labeled multi-view data. |
| 270 | Learning High-Order Task Relationships in Multi-Task Learning | Yu Zhang, Dit-Yan Yeung | In this paper, we propose a new model, called Multi-Task High-Order relationship Learning (MTHOL), which extends in a novel way the use of pairwise task relationships to high-order task relationships. |
| 271 | Lazy Paired Hyper-Parameter Tuning | Alice X. Zheng, Mikhail Bilenko | This paper presents a simple, general technique for improving the efficiency of hyper-parameter tuning by minimizing the number of resampled evaluations at each configuration. |
| 272 | Adaptive Error-Correcting Output Codes | Guoqiang Zhong, Mohamed Cheriet | In this paper, we reformulate the ECOC models from the perspective of multi-task learning, where the binary classifiers are learned in a common subspace of data. |
| 273 | Accurate Probability Calibration for Multiple Classifiers | Leon Wenliang Zhong, James T. Kwok | In this paper, we propose a novel probability calibration approach for such an ensemble of classifiers. |
| 274 | Shifted Subspaces Tracking on Sparse Outlier for Motion Segmentation | Tianyi Zhou, Dacheng Tao | We introduce "shifted subspaces tracking (SST)" to segment the motions and recover their trajectories by exploring the low-rank property of background and the shifted subspace property of each motion. |
| 275 | Persistent Homology: An Introduction and a New Text Representation for Natural Language Processing | Xiaojin Zhu | In response, the first part of this paper presents a tutorial on persistent homology specifically aimed at a broader audience without sacrificing mathematical rigor. |
| 276 | Concept Learning for Cross-Domain Text Classification: A General Probabilistic Framework | Fuzhen Zhuang, Ping Luo, Peifeng Yin, Qing He, Zhongzhi Shi | To this end, we develop a probabilistic model, by which both the shared and distinct concepts can be learned by the EM process which optimizes the data likelihood. |
| 277 | Automatically Generating Problems and Solutions for Natural Deduction | Umair Z. Ahmed, Sumit Gulwani, Amey Karkare | We present two core components, namely solution generation and practice problem generation, for enabling computer-aided education for this important subject domain. |
| 278 | Automated Grading of DFA Constructions | Rajeev Alur, Loris D’Antoni, Sumit Gulwani, Dileep Kini, Mahesh Viswanathan | Our third technique is aimed at capturing mistakes in reading of the problem description. |
| 279 | Misleading Opinions Provided by Advisors: Dishonesty or Subjectivity | Hui Fang, Yang Bao, Jie Zhang | In this paper, we propose a novel probabilistic graphical trust model to separately consider these two factors, involving three types of latent variables: benevolence, integrity and competence of advisors, trust propensity of users, and subjectivity difference between users and advisors. |
| 280 | Personalized Diagnosis for Over-Constrained Problems | Alexander Felfernig, Monika Schubert, Stefan Reiterer | In this paper we introduce techniques that support the calculation of personalized diagnoses for inconsistent constraint sets. |
| 281 | A Brain-Computer Interface to a Plan-Based Narrative | Stephen W. Gilroy, Julie Porteous, Fred Charles, Marc Cavazza, Eyal Soreq, Gal Raz, Limor Ikar, Ayelet Or-Borichov, Udi Ben-Arie, Ilana Klovatch, Talma Hendler | We demonstrate this with a novel Brain-Computer Interface (BCI) design, incorporating empathy for a main character derived from brain signals within filmic conceptions of narrative which drives generation using planning techniques. |
| 282 | Robust Median Reversion Strategy for On-Line Portfolio Selection | Dingjiang Huang, Junlong Zhou, Bin Li, Steven C. H. Hoi, Shuigeng Zhou | To overcome the limitation, we propose to exploit the reversion phenomenon by robust $L_1$-median estimator, and design a novel on-line portfolio selection strategy named "Robust Median Reversion" (RMR), which makes optimal portfolios based on the improved reversion estimation. |
| 283 | A Cutoff Technique for the Verification of Parameterised Interpreted Systems with Parameterised Environments | Panagiotis Kouvaros, Alessio Lomuscio | We present an implementation and discuss experimental results. |
| 284 | TutorialPlan: Automated Tutorial Generation from CAD Drawings | Wei Li, Yuanlin Zhang, George Fitzmaurice | This paper introduces an approach which automatically generates software tutorials using the digital artifacts produced by the users of a software program. |
| 285 | Probabilistic Equivalence Verification Approach for Automatic Mathematical Solution Assessment | Minh Luan Nguyen, Siu Cheung Hui, Alvis C. M. Fong | In this paper, we propose an effective Probabilistic Equivalence Verification (PEV) approach for automatic mathematical solution assessment. |
| 286 | Predicting Human Strategic Decisions Using Facial Expressions | Noam Peled, Moshe Bitan, Joseph Keshet, Sarit Kraus | This work proposes a method for predicting people’s strategic decisions based on their facial expressions. |
| 287 | Employing Batch Reinforcement Learning to Control Gene Regulation without Explicitly Constructing Gene Regulatory Networks | Utku Sirin, Faruk Polat, Reda Alhajj | In this work, we propose a method to control GRNs by using Batch Mode Reinforcement Learning (Batch RL). |
| 288 | Protein Function Prediction via Laplacian Network Partitioning Incorporating Function Category Correlations | Hua Wang, Heng Huang, Chris Ding | To address this challenge, we propose a novel Laplacian Network Partitioning incorporating function category Correlations (LNPC) method to predict protein function on proteinprotein interaction (PPI) networks by optimizing a Laplacian based quotient objective function that seeks the optimal network configuration to maximize consistent function assignments over edges on the whole graph. |
| 289 | Identifying Useful Human Correction Feedback from an On-line Machine Translation Service | Alberto Barrón-Cedeño, Lluís Màrquez, Carlos A. Henríquez Q., Lluís Formiga, Enrique Romero, Jonathan May | We present a study on automatic feedback filtering in a real weblog collected from Reverso.net. |
| 290 | Mining for Analogous Tuples from an Entity-Relation Graph | Danushka Bollegala, Mitsuru Kusumoto, Yuichi Yoshida, Ken-ichi Kawarabayashi | We pro- pose a method to efficiently identify analogous entity tuples from a given entity-relation graph. |
| 291 | Leveraging Multi-Domain Prior Knowledge in Topic Models | Zhiyuan Chen, Arjun Mukherjee, Bing Liu, Meichun Hsu, Malu Castellanos, Riddhiman Ghosh | In this paper, we go one step further to study how the prior knowledge from other domains can be exploited to help topic modeling in the new domain. |
| 292 | Learning Topical Translation Model for Microblog Hashtag Suggestion | Zhuoye Ding, Xipeng Qiu, Qi Zhang, Xuanjing Huang | To address this problem, in this work, we propose a topical translation model for microblog hashtag suggestion. |
| 293 | Smoothing for Bracketing Induction | Xiangyu Duan, Min Zhang, Wenliang Chen | Various kinds of HSS are proposed in this paper. |
| 294 | Crowdsourcing-Assisted Query Structure Interpretation | Jun Han, Ju Fan, Lizhu Zhou | To address the problem, we introduce a human-machine hybrid method by utilizing crowdsourcing platforms. |
| 295 | PPSGen: Learning to Generate Presentation Slides for Academic Papers | Yue Hu, Xiaojun Wan | In this paper, we investigate a very challenging task of automatically generating presentation slides for academic papers. |
| 296 | End-to-End Coreference Resolution for Clinical Narratives | Prateek Jindal, Dan Roth | We present a principled framework to incorporate knowledge-based constraints in the coreference model. |
| 297 | A Clause-Level Hybrid Approach to Chinese Empty Element Recovery | Fang Kong, Guodong Zhou | In comparison, this paper proposes a clause-level hybrid approach to address specific problems in Chinese EE recovery, which recovers EEs in Chinese language from the clause perspective and integrates the advantages of both linear tagging and structured parsing. |
| 298 | Joint Modeling of Argument Identification and Role Determination in Chinese Event Extraction with Discourse-Level Information | Peifeng Li, Qiaoming Zhu, Guodong Zhou | This paper proposes a discourse-level joint model of argument identification and role determination to infer those inter-sentence arguments in a discourse. |
| 299 | Active Learning for Cross-Domain Sentiment Classification | Shoushan Li, Yunxia Xue, Zhongqing Wang, Guodong Zhou | In this paper, we suggest to perform active learning for cross-domain sentiment classification by actively selecting a smallamount of labeled data in the target domain. |
| 300 | Opinion Target Extraction Using Partially-Supervised Word Alignment Model | Kang Liu, Liheng Xu, Yang Liu, Jun Zhao | This paper proposes a novel approach to extract opinion targets by using partial-supervised word alignment model (PSWAM). |
| 301 | Joint and Coupled Bilingual Topic Model Based Sentence Representations for Language Model Adaptation | Shixiang Lu, Xiaoyin Fu, Wei Wei, Xingyuan Peng, Bo Xu | This paper is concerned with data selection for adapting language model (LM) in statistical machine translation (SMT), and aims to find the LM training sentences that are topic similar to the translation task. |
| 302 | Integrating Syntactic and Semantic Analysis into the Open Information Extraction Paradigm | Andrea Moro, Roberto Navigli | In this paper we present an approach aimed at enriching the Open Information Extraction paradigm with semantic relation ontologization by integrating syntactic and semantic features into its workflow. |
| 303 | Combine Constituent and Dependency Parsing via Reranking | Xiaona Ren, Xiao Chen, Chunyu Kit | This paper presents a reranking approach to combining constituent and dependency parsing, aimed at improving parsing performance on both sides. |
| 304 | Fast Linearization of Tree Kernels over Large-Scale Data | Aliaksei Severyn, Alessandro Moschitti | Unfortunately, higher computational complexity of learning with kernels w.r.t. using explicit feature vectors makes them less attractive for large-scale data.In this paper, we study the latest approaches to solve such problems ranging from feature hashing to reverse kernel engineering and approximate cutting plane training with model compression. |
| 305 | Answer Extraction from Passage Graph for Question Answering | Hong Sun, Nan Duan, Yajuan Duan, Ming Zhou | This paper presents a novel approach to extract answers by fully leveraging connections among different passages. |
| 306 | Instance Selection and Instance Weighting for Cross-Domain Sentiment Classification via PU Learning | Rui Xia, Xuelei Hu, Jianfeng Lu, Jian Yang, Chengqing Zong | To address this problem, a novel approach, based on instance selection and instance weighting via PU learning, is proposed. |
| 307 | Modeling Lexical Cohesion for Document-Level Machine Translation | Deyi Xiong, Guosheng Ben, Min Zhang, Yajuan Lü, Qun Liu | In this paper we propose three different models to capture lexical cohesion for document-level machine translation: (a) a direct reward model where translation hypotheses are rewarded whenever lexical cohesion devices occur in them, (b) a conditional probability model where the appropriateness of using lexical cohesion devices is measured, and (c) a mutual information trigger model where a lexical cohesion relation is considered as a trigger pair and the strength of the association between the trigger and the triggered item is estimated by mutual information. |
| 308 | A Text Scanning Mechanism Simulating Human Reading Process | Bei Xu, Hai Zhuge | This paper proposes a text scanning mechanism for generating the dynamic impressions of words in text by simulating recall, association and forget processes during reading. |
| 309 | i, Poet: Automatic Chinese Poetry Composition through a Generative Summarization Framework under Constrained Optimization | Rui Yan, Han Jiang, Mirella Lapata, Shou-De Lin, Xueqiang Lv, Xiaoming Li | In this paper, we formulate the poetry composition task as an optimization problem based on a generative summarization framework under several constraints. |
| 310 | Fusion of Word and Letter Based Metrics for Automatic MT Evaluation | Muyun Yang, Junguo Zhu, Sheng Li, Tiejun Zhao | In contrast to the current efforts in leveraging more linguistic information to depict translation quality, this paper takes the thread of combining language independent features for a robust solution to MT evaluation metric. |
| 311 | Improving Function Word Alignment with Frequency and Syntactic Information | Jingyi Zhang, Hai Zhao | This paper proposes a novel approach to improve word alignment by pruning alignments of function words from an existing alignment model with high precision and recall. |
| 312 | Cross Lingual Entity Linking with Bilingual Topic Model | Tao Zhang, Kang Liu, Jun Zhao | This paper presents a general framework for doing cross lingual entity linking by leveraging a large scale and bilingual knowledge base, Wikipedia. |
| 313 | Integrating Semantic Relatedness and Words’ Intrinsic Features for Keyword Extraction | Wei Zhang, Wei Feng, Jianyong Wang | In this work, we tackle the two issues based on the supervised random walk model. |
| 314 | Partial-Tree Linearization: Generalized Word Ordering for Text Synthesis | Yue Zhang | We present partial-tree linearization, a generalized word ordering (i.e. ordering a set of input words into a grammatical and fluent sentence) task for text-to-text applications. |
| 315 | Improving Question Retrieval in Community Question Answering Using World Knowledge | Guangyou Zhou, Yang Liu, Fang Liu, Daojian Zeng, Jun Zhao | In this paper, we focus on the task of question retrieval.The key problem of question retrieval is to measure the similarity between the queried questions and the historical questions which have been solved by other users. |
| 316 | Efficient Latent Structural Perceptron with Hybrid Trees for Semantic Parsing | Junsheng Zhou, Juhong Xu, Weiguang Qu | In this paper, by introducing hybrid tree as a latent structure variable to close the gap between the input sentences and output representations, we formulate semantic parsing as a structured prediction problem, based on the latent variable perceptron model incorporated with a tree edit-distance loss as optimization criterion. |
| 317 | Revisiting Regression in Planning | Vidal Alcázar, Daniel Borrajo, Susana Fernández, Raquel Fuentetaja | In this work we revisit regression in planning with reachability-based heuristics, trying to extrapolate to backward search current lines of research that were not as well understood as they are now. |
| 318 | Bridging the Gap Between Refinement and Heuristics in Abstraction | Christer Bäckström, Peter Jonsson | We present an extensive study of how such metric properties relate to the properties in the original framework, revealing a number of connections between the refinement and heuristic approaches. |
| 319 | An Admissible Heuristic for SAS+ Planning Obtained from the State Equation | Blai Bonet | In this paper we present a new admissible heuristic that is obtained from the state equation associated to the Petri-net representation of the planning problem. |
| 320 | Causal Belief Decomposition for Planning with Sensing: Completeness Results and Practical Approximation | Blai Bonet, Hector Geffner | In this work, we extend this result both theoretically and practically. |
| 321 | Isomorph-Free Branch and Bound Search for Finite State Controllers | Marek Grześ, Pascal Poupart, Jesse Hoey | In this paper, we propose a new branch and bound technique to search for a good controller. |
| 322 | Optimal Delete-Relaxed (and Semi-Relaxed) Planning with Conditional Effects | Patrik Haslum | We present an incremental compilation approach that enables these methods to be applied to problems with conditional effects, which none of them support natively. |
| 323 | Interactive POMDP Lite: Towards Practical Planning to Predict and Exploit Intentions for Interacting with Self-Interested Agents | Trong Nghia Hoang, Kian Hsiang Low | A key challenge in non-cooperative multi-agent systems is that of developing efficient planning algorithms for intelligent agents to interact and perform effectively among boundedly rational, self-interested agents (e.g., humans). |
| 324 | Controlling the Hypothesis Space in Probabilistic Plan Recognition | Froduald Kabanza, Julien Filion, Abder Rezak Benaskeur, Hengameh Irandoust | This paper presents a heuristic weighted model counting algorithm that limits the number of generated plan execution models in order to recognize goals quickly by computing their lower and upper bound likelihoods. |
| 325 | Lifelong Learning for Acquiring the Wisdom of the Crowd | Ece Kamar, Ashish Kapoor, Eric Horvitz | We present methods that can be used to guide the collection of data for enhancing the competency of such predictive models while using the models to provide a base crowdsourcing service. |
| 326 | Pareto-Based Multiobjective AI Planning | Mostepha Khouadjia, Marc Schoenauer, Vincent Vidal, Johann Dréo, Pierre Savéant | The only approaches to multiobjective AI Planning rely on metrics, that can incorporate several objectives in some linear combinations, and metric sensitive planners, that are able to give different plans for different metrics, and hence to eventually approximate the Pareto front of the multiobjective problem, i.e. the set of optimal trade-offs between the antagonistic objectives. |
| 327 | Flexible Execution of Partial Order Plans with Temporal Constraints | Christian Muise, J. Christopher Beck, Sheila A. McIlraith | We propose a unified approach to plan execution and schedule dispatching that converts a plan, which has been augmented with temporal constraints, into a policy for dispatching. |
| 328 | Towards a Second Generation Random Walk Planner: An Experimental Exploration | Hootan Nakhost, Martin Müller | The work presented here aims to exploit the experience gained from building those systems. |
| 329 | Fair LTL Synthesis for Non-Deterministic Systems Using Strong Cyclic Planners | Fabio Patrizi, Nir Lipovetzky, Hector Geffner | We consider the problem of planning in environments where the state is fully observable, actions have non-deterministic effects, and plans must generate infinite state trajectories for achieving a large class of LTL goals. |
| 330 | Fault-Tolerant Planning under Uncertainty | Luis Pineda, Yi Lu, Shlomo Zilberstein, Claudia V. Goldman | We introduce an approach to plan for a bounded number of faults and analyze its theoretical properties. |
| 331 | Getting the Most Out of Pattern Databases for Classical Planning | Florian Pommerening, Gabriele Röger, Malte Helmert | We show how stronger heuristic estimates can be obtained through linear programming. |
| 332 | Computing Upper Bounds on Lengths of Transition Sequences | Jussi Rintanen, Charles Orgill Gretton | We describe an approach to computing upper bounds on the lengths of solutions to reachability problems in transition systems. |
| 333 | Exploring Knowledge Engineering Strategies in Designing and Modelling a Road Traffic Accident Management Domain | Mohammad M. Shah, Lukáš Chrpa, Diane Kitchin, Thomas L. McCluskey, Mauro Vallati | This paper seeks to investigate this process using as a case study a road traffic accident management domain. |
| 334 | The GoDeL Planning System: A More Perfect Union of Domain-Independent and Hierarchical Planning | Vikas Shivashankar, Ron Alford, Ugur Kuter, Dana Nau | To provide a principled way to overcome this difficulty, we define a simple formalism that extends classical planning to include problem decomposition using methods, and a planning algorithm based on this formalism. |
| 335 | Plan Quality Optimisation via Block Decomposition | Fazlul Hasan Siddiqui, Patrik Haslum | We present a new method of continuing plan improvement, that works by repeatedly decomposing a given plan into subplans and optimising each subplan locally. |
| 336 | Symbolic Merge-and-Shrink for Cost-Optimal Planning | Álvaro Torralba, Carlos Linares López, Daniel Borrajo | We present a combination of these techniques, Symbolic Merge-and-Shrink (SM&S), which uses M&S abstractions as a relaxation criterion for a symbolic backward search. |
| 337 | Problem Splitting Using Heuristic Search in Landmark Orderings | Simon Vernhes, Guillaume Infantes, Vincent Vidal | In this paper, we revisit the idea of splitting a planning problem into subproblems hopefully easier to solve with the help of landmark analysis. |
| 338 | Run-Time Improvement of Point-Based POMDP Policies | Minlue Wang, Richard Dearden | In this paper we explore the use of an on-line plan repair approach to overcome this difficulty. |
| 339 | Interactive Value Iteration for Markov Decision Processes with Unknown Rewards | Paul Weng, Bruno Zanuttini | To tackle the potentially hard task of defining the reward function in a Markov Decision Process, we propose a new approach, based on Value Iteration, which interweaves the elicitation and optimization phases. |
| 340 | Flexibility and Decoupling in the Simple Temporal Problem | Michel Wilson, Tomas Klos, Cees Witteveen, Bob Huisman | In this paper we concentrate on finding a suitable metric to determine the flexibility of a Simple Temporal Problem (STP). |
| 341 | Continuously Relaxing Over-Constrained Conditional Temporal Problems through Generalized Conflict Learning and Resolution | Peng Yu, Brian Williams | We present the Best-first Conflict-Directed Relaxation (BCDR) algorithm for enumerating the best continuous relaxation for an over-constrained conditional temporal problem with controllable choices. |
| 342 | Robust Optimization for Hybrid MDPs with State-Dependent Noise | Zahra Zamani, Scott Sanner, Karina Valdivia Delgado, Leliane Nunes de Barros | In this paper, we work around limitations of previous solutions by adopting a robust optimization approach in which Nature is allowed to adversarially determine transition noise within pre-specified confidence intervals. |
| 343 | Action-Model Acquisition from Noisy Plan Traces | Hankz Hankui Zhuo, Subbarao Kambhampati | In this paper, we aim to remove this assumption, allowing plan traces to be with noise. We create a set of random variables to capture the possible correct plan traces behind the observed noisy ones, and build a graphical model to describe the physics of the domain. |
| 344 | Refining Incomplete Planning Domain Models through Plan Traces | Hankz Hankui Zhuo, Tuan Nguyen, Subbarao Kambhampati | In this paper we propose and evaluate a method for doing this. |
| 345 | Handling Open Knowledge for Service Robots | Xiaoping Chen, Jianmin Ji, Zhiqiang Sui, Jiongkun Xie | In this paper, the core problem is formalized and the complexity results of the main reasoning issues are provided. |
| 346 | Human Action Recognition Using a Temporal Hierarchy of Covariance Descriptors on 3D Joint Locations | Mohamed E. Hussein, Marwan Torki, Mohammad A. Gowayyed, Motaz El-Saban | In this paper, we present a novel approach to human action recognition from 3D skeleton sequences extracted from depth data. |
| 347 | Rolling Dispersion for Robot Teams | Elizabeth A. Jensen, Maria Gini | We propose a rolling dispersion algorithm, which makes use of a small number of robots and achieves full exploration. |
| 348 | Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning | Maxime Latulippe, Alexandre Drouin, Philippe Giguère, François Laviolette | In this paper, we are interested in improving this scan alignment in challenging natural environments. |
| 349 | Upper Confidence Weighted Learning for Efficient Exploration in Multiclass Prediction with Binary Feedback | Hung Ngo, Matthew Luciw, Ngo Anh Vien, Jürgen Schmidhuber | We introduce a novel algorithm called Upper Confidence Weighted Learning (UCWL) for online multiclass learning from binary feedback. |
| 350 | Towards Active Event Recognition | Dimitri Ognibene, Yiannis Demiris | It requires an integrated solution for tracking, exploration and recognition, which traditionally have been seen as separate problems in active vision.We propose a probabilistic generative framework based on a mixture of Kalman filters and information gain maximisation that uses predictions in both recognition and attention-control. |
| 351 | Hierarchical Object Discovery and Dense Modelling from Motion Cues in RGB-D Video | Jörg Stückler, Sven Behnke | In this paper, we propose a novel method for object discovery and dense modelling in RGB-D image sequences using motion cues. |
| 352 | Learning Visual Symbols for Parsing Human Poses in Images | Fang Wang, Yi Li | Our goal is to learn self-contained body part representations from images, which we call visual symbols, and their symbol-wise geometric contexts in this parsing process. |
| 353 | A Consensual Linear Opinion Pool | Arthur Carvalho, Kate Larson | In this paper, we propose a pooling method to aggregate expert opinions. |
| 354 | An Exact Algorithm for Computing the Same-Decision Probability | Suming Chen, Arthur Choi, Adnan Darwiche | We propose the first exact algorithm for computing the SDP in this paper, and demonstrate its effectiveness on several real and synthetic networks. |
| 355 | Probabilistic Reasoning with Undefined Properties in Ontologically-Based Belief Networks | Chia-Li Kuo, David Buchman, Arzoo Katiyar, David Poole | In this paper, we propose an alternative, ontologically-based belief networks, where all properties are only used when they are defined, and we show how probabilistic reasoning can be carried out without explicitly using the value "undefined" during inference. |
| 356 | Inference for a New Probabilistic Constraint Logic | Steffen Michels, Arjen Hommersom, Peter J. F. Lucas, Marina Velikova, Pieter Koopman | In this paper, we propose a new probabilistic constraint logic programming language, which combines constraint logic programming with probabilistic reasoning. |
| 357 | Map Matching with Inverse Reinforcement Learning | Takayuki Osogami, Rudy Raymond | We study map-matching, the problem of estimating the route that is traveled by a vehicle, where the points observed with the Global Positioning System are available. |
| 358 | Accurate Integration of Crowdsourced Labels Using Workers’ Self-Reported Confidence Scores | Satoshi Oyama, Yukino Baba, Yuko Sakurai, Hisashi Kashima | We have developed a method for using confidence scores to integrate labels provided by crowdsourcing workers. |
| 359 | Look versus Leap: Computing Value of Information with High-Dimensional Streaming Evidence | Stephanie Rosenthal, Dan Bohus, Ece Kamar, Eric Horvitz | We describe a belief projection approach to reasoning about information value in these settings, using models for inferring future beliefs over states given streaming evidence. |
| 360 | The Inclusion-Exclusion Rule and Its Application to the Junction Tree Algorithm | David Smith, Vibhav Gogate | In this paper, we consider the inclusion-exclusion rule – a known yet seldom used rule of probabilistic inference. |
| 361 | Sample Complexity of Risk-Averse Bandit-Arm Selection | Jia Yuan Yu, Evdokia Nikolova | We present algorithms to minimize the risk over a single and multiple time periods, along with PAC accuracy guarantees given a finite number of reward samples. |
| 362 | A Generalization of SAT and #SAT for Robust Policy Evaluation | Erik Zawadzki, André Platzer, Geoffery J. Gordon | Here, we examine an expressive new language, #∃SAT, that generalizes both of these languages. |
| 363 | Link Label Prediction in Signed Social Networks | Priyanka Agrawal, Vikas K. Garg, Ramasuri Narayanam | In this paper, we focus on online signed social networks where positive interactions among the users signify friendship or approval, whereas negative interactions indicate antagonism or disapproval. We introduce a novel problem which we call the link label prediction problem: Given the information about signs of certain links in a social network, we want to learn the nature of relationships that exist among the users by predicting the sign, positive or negative, of the remaining links. |
| 364 | Multi-View K-Means Clustering on Big Data | Xiao Cai, Feiping Nie, Heng Huang | In this paper, we propose a new robust large-scale multi-view clustering method to integrate heterogeneous representations of large-scale data. |
| 365 | Where You Like to Go Next: Successive Point-of-Interest Recommendation | Chen Cheng, Haiqin Yang, Michael R. Lyu, Irwin King | In this paper, we consider the task of successive personalized POI recommendation in LBSNs, which is a much harder task than standard personalized POI recommendation or prediction. |
| 366 | Celebrity Recommendation with Collaborative Social Topic Regression | Xuetao Ding, Xiaoming Jin, Yujia Li, Lianghao Li | In this paper, we proposed a unified hierarchical Bayesian model to recommend celebrities to the general users. |
| 367 | A Novel Bayesian Similarity Measure for Recommender Systems | Guibing Guo, Jie Zhang, Neil Yorke-Smith | To solve these issues, we propose a novel Bayesian similarity measure based on the Dirichlet distribution, taking into consideration both the direction and length of rating vectors. |
| 368 | Cross-Domain Collaborative Filtering via Bilinear Multilevel Analysis | Liang Hu, Jian Cao, Guandong Xu, Jie Wang, Zhiping Gu, Longbing Cao | To address this problem, we propose a novel CDCF model, the Bilinear Multilevel Analysis (BLMA), which seamlessly introduces multilevel analysis theory to the most successful collaborative filtering method, matrix factorization (MF). |
| 369 | Social Spammer Detection in Microblogging | Xia Hu, Jiliang Tang, Yanchao Zhang, Huan Liu | In this paper, we investigate how to collectively use network and content information to perform effective social spammer detection in microblogging. |
| 370 | Listening to the Crowd: Automated Analysis of Events via Aggregated Twitter Sentiment | Yuheng Hu, Fei Wang, Subbarao Kambhampati | In this work, we consider the problem of identifying the segments and topics of an event that garnered praise or criticism, according to aggregated Twitter responses. |
| 371 | Social Trust Prediction Using Rank-k Matrix Recovery | Jin Huang, Feiping Nie, Heng Huang, Yu Lei, Chris Ding | In this paper, instead of using trace norm minimization, we propose a new robust rank-k matrix completion method, which explicitly seeks a matrix with exact rank. |
| 372 | Context-Dependent Conceptualization | Dongwoo Kim, Haixun Wang, Alice Oh | To overcome this limitation, we propose a framework in which we harness the power of a probabilistic topic model which inherently captures the semantic relations between words. |
| 373 | Predicting Knowledge in an Ontology Stream | Freddy Lécué, Jeff Z. Pan | We tackle predictive reasoning as a correlation and interpretation of past semantics-augmented data over exogenous ontology streams. |
| 374 | A Unified Framework for Reputation Estimation in Online Rating Systems | Guang Ling, Irwin King, Michael R. Lyu | In this paper, we propose a unified framework for computing the reputation score of a user, given only users’ ratings on items. |
| 375 | Synthesizing Union Tables from the Web | Xiao Ling, Alon Halevy, Fei Wu, Cong Yu | In this paper, we argue that those efforts only scratch the surface of the true value of structured data on the Web, and study the challenging problem of synthesizing tables from the Web, i.e., producing never-before-seen tables from raw tables on the Web. |
| 376 | Recommendation Using Textual Opinions | Claudiu-Cristian Musat, Yizhong Liang, Boi Faltings | We propose a new technique, topic profile collaborative filtering, where we build user profiles from users’ review texts and use these profiles to filter other review texts with the eyes of this user. |
| 377 | GBPR: Group Preference Based Bayesian Personalized Ranking for One-Class Collaborative Filtering | Weike Pan, Li Chen | As a response, we propose a new and improved assumption, group Bayesian personalized ranking (GBPR), via introducing richer interactions among users. |
| 378 | Promoting Diversity in Recommendation by Entropy Regularizer | Lijing Qin, Xiaoyan Zhu | In this paper, we propose an entropy regularizer to capture the notion of diversity. |
| 379 | SCMF: Sparse Covariance Matrix Factorization for Collaborative Filtering | Jianping Shi, Naiyan Wang, Yang Xia, Dit-Yan Yeung, Irwin King, Jiaya Jia | Based on the findings, we propose an MF model with a sparse covariance prior which favors a sparse yet non-diagonal covariance matrix. |
| 380 | Exploiting Local and Global Social Context for Recommendation | Jiliang Tang, Xia Hu, Huiji Gao, Huan Liu | Users are likely to seek suggestions from both their local friends and users with high global reputations, motivating us to exploit social relations from local and global perspectives for online recommender systems in this paper. |
| 381 | Collaborative Topic Regression with Social Regularization for Tag Recommendation | Hao Wang, Binyi Chen, Wu-Jun Li | Collaborative Topic Regression with Social Regularization for Tag Recommendation |
| 382 | Online Egocentric Models for Citation Networks | Hao Wang, Wu-Jun Li | In this paper, we propose a novel model,called online egocentric model (OEM), to learn time-varying parameters and node features for evolving citation networks. |
| 383 | Boosting Cross-Lingual Knowledge Linking via Concept Annotation | Zhichun Wang, Juanzi Li, Jie Tang | In this paper, we propose an approach that boosts cross-lingual knowledge linking by concept annotation. |
| 384 | PageRank with Priors: An Influence Propagation Perspective | Biao Xiang, Qi Liu, Enhong Chen, Hui Xiong, Yi Zheng, Yu Yang | To this end, in this paper, we provide a focused study on understanding of PageRank as well as the relationship between PageRank and social influence analysis. |
| 385 | Social Collaborative Filtering by Trust | Bo Yang, Yu Lei, Dayou Liu, Jiming Liu | To address such issues, this article proposes a novel method, trying to improve the performance of collaborative filtering recommendation by means of elaborately integrating twofold sparse information, the conventional rating data given by users and the social trust network among the same users. |
| 386 | Parametric Local Multimodal Hashing for Cross-View Similarity Search | Deming Zhai, Hong Chang, Yi Zhen, Xianming Liu, Xilin Chen, Wen Gao | In this paper, we study HFL in the context of multimodal data for cross-view similarity search. |
| 387 | Social Influence Locality for Modeling Retweeting Behaviors | Jing Zhang, Biao Liu, Jie Tang, Ting Chen, Juanzi Li | We study an interesting phenomenon of social influence locality in a large microblogging network, which suggests that users’ behaviors are mainly influenced by close friends in their ego networks. |
| 388 | Automatic Name-Face Alignment to Enable Cross-Media News Retrieval | Yuejie Zhang, Wei Wu, Yang Li, Cheng Jin, Xiangyang Xue, Jianping Fan | A new algorithm is developed in this paper to support automatic name-face alignment for achieving more accurate cross-media news retrieval. |
| 389 | Assessing the Resilience of Socio-Ecosystems: Coupling Viability Theory and Active Learning with kd-Trees — Application to Bilingual Societies | Isabelle Alvarez, Ricardo de Aldama, Sophie Martin, Romain Reuillon | This paper proposes a new algorithm to compute the resilience of a social system or an ecosystem when it is defined in the framework of the mathematical viability theory. |
| 390 | Towards Understanding Global Spread of Disease from Everyday Interpersonal Interactions | Sean Brennan, Adam Sadilek, Henry Kautz | By contrast, this paper explores how individuals contribute to the global spread of disease. |
| 391 | Short-Term Wind Power Forecasting Using Gaussian Processes | Niya Chen, Zheng Qian, Xiaofeng Meng, Ian T. Nabney | In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. |
| 392 | Semi-Supervised Learning for Integration of Aerosol Predictions from Multiple Satellite Instruments | Nemanja Djuric, Lakesh Kansakar, Slobodan Vucetic | We present a method for learning how to aggregate AOD estimations from multiple satellite instruments into a more accurate estimation. |
| 393 | Deep Sparse Coding Based Recursive Disaggregation Model for Water Conservation | Haili Dong, Bingsheng Wang, Chang-Tien Lu | In this paper, a Deep Sparse Coding based Recursive Disaggregation Model (DSCRDM) is proposed for water conservation. We design a recursive decomposition structure to perform the disaggregation task, and introduce sequential set to capture its characteristics. |
| 394 | Optimal Pricing for Improving Efficiency of Taxi Systems | Jiarui Gan, Bo An, Haizhong Wang, Xiaoming Sun, Zhongzhi Shi | To resolve this problem, we propose a new pricing scheme to provide taxi drivers with extra incentives to work during peak hours. |
| 395 | Estimating Reference Evapotranspiration for Irrigation Management in the Texas High Plains | Daniel Holman, Mohan Sridharan, Prasanna Gowda, Dana Porter, Thomas Marek, Terry Howell, Jerry Moorhead | The objective of our research is to enable the use of alternative data sources, adapting sophisticated machine learning algorithms such as Gaussian process models and neural networks to discover and model the nonlinear relationships between non-ET weather station data and the reference ET computed by ET networks. |
| 396 | Information Fusion Based Learning for Frugal Traffic State Sensing | Vikas Joshi, Nithya Rajamani, Takayuki Katsuki, Naveen Prathapaneni, L. V. Subramaniam | In this paper, we demonstrate a fusion based learning approach to classify the traffic states using low cost audio and image data analysis using real world dataset. |
| 397 | A Multi-Objective Memetic Algorithm for Vehicle Resource Allocation in Sustainable Transportation Planning | Hoong Chuin Lau, Lucas Agussurja, Shih-Fen Cheng, Pang Jin Tan | We formulate the bi-objective optimization problem exactly and design a memetic algorithm to efficiently derive an approximate Pareto front. |
| 398 | Crowdsourcing Backdoor Identification for Combinatorial Optimization | Ronan Le Bras, Richard Bernstein, Carla P. Gomes, Bart Selman, R. Bruce van Dover | We describe our work in the context of the domain of materials discovery. |
| 399 | Evolution of Common-Pool Resources and Social Welfare in Structured Populations | Jean-Sébastien Lerat, The Anh Han, Tom Lenaerts | The present study provides for the first time a detailed analysis of the evolutionary dynamics of consumption strategies in finite populations, focusing on the interplay between the resource levels and preferred consumption strategies. |
| 400 | Tag-Weighted Topic Model for Mining Semi-Structured Documents | Shuangyin Li, Jiefei Li, Rong Pan | In this paper, we propose a novel method to model tagged documents by a topic model, called Tag-Weighted Topic Model (TWTM). |
| 401 | Manifold Alignment Based on Sparse Local Structures of More Corresponding Pairs | Xiaojie Li, Jian Cheng Lv, Zhang Yi | This paper proposes an approach to obtain more and reliable corresponding pairs in terms of local structure correspondence. |
| 402 | A Global Constrained Optimization Method for Designing Road Networks with Small Diameters | Teng Ma, Yuexian Hou, Xiaozhao Zhao, Dawei Song | Based on this observation, we propose a set of constrained convex models for designing road networks with small diameters. |
| 403 | Bayesian Joint Inversions for the Exploration of Earth Resources | Alistair Reid, Simon O’Callaghan, Edwin V. Bonilla, Lachlan McCalman, Tim Rawling, Fabio Ramos | We propose a machine learning approach to geophysical inversion problems for the exploration of earth resources. |
| 404 | Dynamic Taxi and Ridesharing: A Framework and Heuristics for the Optimization Problem | Douglas O. Santos, Eduardo C. Xavier | In this paper we study a dynamic problem of ridesharing and taxi sharing with time windows. |
| 405 | An Active Learning Approach to Home Heating in the Smart Grid | Mike Shann, Sven Seuken | We propose an active learning approach to adjust the home temperature in a semi-automatic way. |
| 406 | Planning with MIP for Supply Restoration in Power Distribution Systems | Sylvie Thiébaux, Carleton Coffrin, Hassan Hijazi, John Slaney | The key contributions of the paper are (1) a flexible mixed-integer programming framework for solving PSR, (2) a model decomposition to obtain high-quality solutions within the required time constraints, and (3) an experimental validation of the potential benefits of the proposed PSR operations. |
| 407 | Forecasting Multi-Appliance Usage for Smart Home Energy Management | Ngoc Cuong Truong, James McInerney, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn | We address the problem of forecasting the usage of multiple electrical appliances by domestic users, with the aim of providing suggestions about the best time to run appliances in order to reduce carbon emissions and save money (assuming time-of-use pricing), while minimising the impact on the users’ daily habits.An important challenge related to this problem is the modelling the everyday routine of the consumers and of the inter-dependencies between the use of different appliances. |
| 408 | Randomized Load Control: A Simple Distributed Approach for Scheduling Smart Appliances | Menkes van den Briel, Paul Scott, Sylvie Thiébaux | We present randomized load control, a simple distributed approach for scheduling smart appliances. |
| 409 | Parameter Learning for Latent Network Diffusion | Xiaojian Wu, Akshat Kumar, Daniel Sheldon, Shlomo Zilberstein | We develop an EM algorithm to address parameter learning in such settings. |
| 410 | Towards Effective Prioritizing Water Pipe Replacement and Rehabilitation | Junchi Yan, Yu Wang, Ke Zhou, Jin Huang, Chunhua Tian, Hongyuan Zha, Weishan Dong | This paper presents an already-deployed industrial computational system for pipe failure prediction. |
| 411 | Improved Integer Programming Approaches for Chance-Constrained Stochastic Programming | Hiroki Yanagisawa, Takayuki Osogami | In this paper, we consider the special case of the CCSP in which only the right-hand side vector is random with a discrete distribution having a finite support. |
| 412 | A Hidden Markov Model-Based Acoustic Cicada Detector for Crowdsourced Smartphone Biodiversity Monitoring | Davide Zilli, Oliver Parson, Geoff V. Merrett, Alex Rogers | To address this shortcoming we propose a novel insect detection algorithm based on a hidden Markov model to which we feed as a single feature vector the ratio of two key frequencies extracted through the Goertzel algorithm. |
| 413 | Forecast Oriented Classification of Spatio-Temporal Extreme Events | Zhengzhang Chen, Yusheng Xie, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Nagiza F. Samatova, Alok Choudhary | In this paper, we propose a new supervised machine learning problem, which we call a forecast oriented classification of spatiotemporal extreme events. |
| 414 | Adaptive Management of Migratory Birds under Sea Level Rise | Samuel Nicol, Olivier Buffet, Takuya Iwamura, Iadine Chadès | Existing solution methods used for AM problems assume that the system dynamics are stationary, i.e., described by one of a set of pre-defined models. We provide an ecological dataset and performance metrics for the AM of a network of shorebird species utilizing the East Asian-Australasian flyway given uncertainty about the rate of sea level rise. |
| 415 | Detecting and Tracking Disease Outbreaks by Mining Social Media Data | Yusheng Xie, Zhengzhang Chen, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Alok Choudhary | The challenge we describe in this data paper is how to extract and leverage epidemic outbreak insights from massive amounts of social media data and how this exercise can benefit medical professionals, patients, and policymakers alike. |
| 416 | Twitter-Based User Modeling for News Recommendations | Fabian Abel, Qi Gao, Geert-Jan Houben, Ke Tao | In this paper, we study user modeling on Twitter. |
| 417 | Language-Based Games (Extended Abstract) | Adam Bjorndahl, Joseph Y. Halpern, Rafael Pass | We introduce language-based games, a generalization of psychological games [Geanakoplos, Pearce, and Stacchetti, 1989] that can also capture reference-dependent preferences [Koszegi and Rabin, 2006], which extend the domain of the utility function to "situations", maximal consistent sets in some language. |
| 418 | An Improved Separation of Regular Resolution from Pool Resolution and Clause Learning (Extended Abstract) | Maria Luisa Bonet, Sam Buss | We establish the unexpected power of conflict driven clause learning (CDCL) proof search by proving that the sets of unsatisfiable clauses obtained from the guarded graph tautology principles of Alekhnovich, Johannsen, Pitassi and Urquhart have polynomial size pool resolution refutations that use only input lemmas as learned clauses. |
| 419 | The Complexity of One-Agent Refinement Modal Logic | Laura Bozzelli, Hans van Ditmarsch, Sophie Pinchinat | In this paper we show that RML-satisfiability is ‘only’ singly exponentially harder than ML-satisfiability, the latter being a well-known PSPACE-complete problem. |
| 420 | An Introduction to String Re-Writing Kernel | Fan Bu, Hang Li, Xiaoyan Zhu | In this paper, we propose a new class of kernel functions, referred to as string rewriting kernel, to address the problem. |
| 421 | Optimal Valve Placement in Water Distribution Networks with CLP(FD) | Massimiliano Cattafi, Marco Gavanelli, Maddalena Nonato, Stefano Alvisi, Marco Franchini | This paper presents a new application of logic programming to a real-life problem in hydraulic engineering. |
| 422 | Bayesian Probabilities for Constraint-Based Causal Discovery | Tom Claassen, Tom Heskes | Our aim is to combine the inherent robustness of the Bayesian approach with the theoretical strength and clarity of constraint-based methods. |
| 423 | Satisfiability Modulo Constraint Handling Rules (Extended Abstract) | Gregory James Duck | This paper introduces SMCHR: a tight integration of CHR with a modern Boolean Satisfiability (SAT) solver. |
| 424 | Case Adaptation with Qualitative Algebras | Valmi Dufour-Lussier, Florence Le Ber, Jean Lieber, Laura Martin | This paper proposes an approach for the adaptation of spatial or temporal cases in a case-based reasoning system. |
| 425 | Improving the Effectiveness of Time-Based Display Advertising (Extended Abstract) | Daniel G. Goldstein, R. Preston McAfee, Siddharth Suri | We test and present one schedule that leads to greater total recollection, which advertisers want, and increased revenue, which publishers want. |
| 426 | Preference-Based CBR: General Ideas and Basic Principles | Eyke Hüllermeier, Weiwei Cheng | In this paper, we outline the basic ideas of preference-based CBR and sketch a formal framework for realizing these ideas. |
| 427 | Sound, Complete, and Minimal Query Rewriting for Existential Rules | Mélanie König, Michel Leclère, Marie-Laure Mugnier, Michaël Thomazo | We address the issue of Ontology-Based Data Access which consists of exploiting the semantics expressed in ontologies while querying data. |
| 428 | Collaborative Filtering on Ordinal User Feedback | Yehuda Koren, Joseph Sill | We propose a collaborative filtering (CF) recommendation framework which is based on viewing user feedback on products as ordinal, rather than the more common numerical view. |
| 429 | Three Semantics for the Core of the Distributed Ontology Language (Extended Abstract) | Till Mossakowski, Christoph Lange, Oliver Kutz | We present the abstract syntax of these meta-level constructs, with three alternative semantics: direct, translational, and collapsed semantics. |
| 430 | Discovering Alignments in Ontologies of Linked Data | Rahul Parundekar, Craig A. Knoblock, José Luis Ambite | We address this problem by automatically finding alignments between concepts from multiple linked data sources. |
| 431 | A New Trajectory Deformation Algorithm Based on Affine Transformations | Quang-Cuong Pham, Yoshihiko Nakamura | We propose a method to deform robot trajectories based on affine transformations. |
| 432 | A Case-Based Solution to the Cold-Start Problem in Group Recommenders | Lara Quijano-Sánchez, Derek Bridge, Belén Díaz-Agudo, Juan Antonio Recio-García | In this paper we offer a potential solution to the cold-start problem in group recommender systems. |
| 433 | Data Mining a Trillion Time Series Subsequences under Dynamic Time Warping | Thanawin Rakthanmanon, Bilson Campana, Abdullah Mueen, Gustavo Batista, Brandon Westover, Qiang Zhu, Jesin Zakaria, Eamonn Keogh | In this work we show that by using a combination of four novel ideas we can search and mine truly massive time series for the first time. |
| 434 | On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference (Extended Abstract) | Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar | We present a reformulation of the stochastic optimal control problem in terms of KL divergence minimisation, not only providing a unifying perspective of previous approaches in this area, but also demonstrating that the formalism leads to novel practical approaches to the control problem. |
| 435 | At Home with Agents: Exploring Attitudes Towards Future Smart Energy Infrastructures | Tom A. Rodden, Joel E. Fischer, Nadia Pantidi, Khaled Bachour, Stuart Moran | This paper considers how consumers might relate to future smart energy grids. |
| 436 | Decision Generalisation from Game Logs in No Limit Texas Hold’em | Jonathan Rubin, Ian Watson | Given a set of data, recorded by observing the decisions of an expert player, we present a case-based framework that allows the successful generalisation of those decisions in the game of no limit Texas Hold’em. |
| 437 | Modeling the Interplay of People’s Location, Interactions, and Social Ties | Adam Sadilek, Henry Kautz, Jeffrey P. Bigham | We present and evaluate Flap, a system that solves two intimately related tasks: link and location prediction in online social networks. |
| 438 | Active Evaluation of Ranking Functions Based on Graded Relevance (Extended Abstract) | Christoph Sawade, Steffen Bickel, Timo von Oertzen, Tobias Scheffer, Niels Landwehr | We address the problem of estimating ranking performance as accurately as possible on a fixed labeling budget. |
| 439 | CLiMF: Collaborative Less-Is-More Filtering | Yue Shi, Alexandros Karatzoglou, Linas Baltrunas, Martha Larson, Nuria Oliver, Alan Hanjalic | In this paper we tackle the problem of recommendation in the scenarios with binary relevance data, when only a few (k) items are recommended to individual users. |
| 440 | Statistical Parsing with Probabilistic Symbol-Refined Tree Substitution Grammars | Hiroyuki Shindo, Yusuke Miyao, Akinori Fujino, Masaaki Nagata | We present probabilistic Symbol-Refined Tree Substitution Grammars (SR-TSG) for statistical parsing of natural language sentences. |
| 441 | Exact Recovery of Sparsely-Used Dictionaries | Daniel A. Spielman, Huan Wang, John Wright | We consider the problem of learning sparsely used dictionaries with an arbitrary square dictionary and a random, sparse coefficient matrix. |
| 442 | The RoboEarth Language: Representing and Exchanging Knowledge about Actions, Objects, and Environments (Extended Abstract) | Moritz Tenorth, Alexander Perzylo, Reinhard Lafrenz, Michael Beetz | In this paper, we report on the formal language we developed for encoding this information and present our approaches to solve the inference problems related to finding information, to determining if information is usable by a robot, and to grounding it on the robot platform. |
| 443 | Socioscope: Spatio-Temporal Signal Recovery from Social Media (Extended Abstract) | Jun-Ming Xu, Aniruddha Bhargava, Robert Nowak, Xiaojin Zhu | We address these issues by formulating signal recovery as a Poisson point process estimation problem. |
| 444 | Using Strategic Logics to Reason about Agent Programs | Nitin Yadav, Sebastian Sardina | We propose a variant of Alternating-time Temporal Logic (ATL) grounded in the agents’ operational know-how, as defined by their libraries of abstract plans. |
| 445 | User-Centered Programming by Demonstration: Stylistic Elements of Behavior | James E. Young, Kentaro Ishii, Takeo Igarashi, Ehud Sharlin | In this paper we present a user-centered programming by demonstration project for authoring interactive robotic locomotion style. |
| 446 | Scalable Dynamic Nonparametric Bayesian Models of Content and Users | Amr Ahmed, Eric Xing | In this paper, we addresses the problem of information organization of online document collections, and provide algorithms that create a structured representation of the otherwise unstructured content. |
| 447 | Improving Combinatorial Optimization: Extended Abstract | Geoffrey Chu | In the thesis, we present important contributions to several different areas of combinatorial optimization, including nogood learning, symmetry breaking, dominance, relaxations and parallelization. |
| 448 | Cultural Diversity for Virtual Characters (Extended Abstract) | Birgit Endrass | This paper proposes a hybrid approach for the generation of culture-specific behaviors in a multiagent system. |
| 449 | Landmark-Based Heuristics and Search Control for Automated Planning (Extended Abstract) | Silvia Richter | This paper summarises several contributions that improve the efficiency of automated planning via heuristic search. |
| 450 | Learning Probabilistic Models for Mobile Manipulation Robots | Jürgen Sturm, Wolfram Burgard | In this paper, we present novel approaches to allow mobile maniplation systems to autonomously adapt to new or changing situations. |
| 451 | Social Norms for Self-Policing Multi-Agent Systems and Virtual Societies (Extended Abstract) | Daniel Villatoro | In this article we summarize the contributions of my dissertation, where we provide an unifying framework for the analysis of social norms in virtual societies, providing an strong emphasis on virtual agents and humans. |
| 452 | Evaluating Indirect Strategies for Chinese–Spanish Statistical Machine Translation: Extended Abstract | Marta R. Costa-jussà, Carlos A. Henríquez, Rafael E. Banchs | The main objective of this work is motivating and involving the research community to work in this important pair of languages given their demographic impact. |
| 453 | Communicating Open Systems (Extended Abstract) | Mark d’Inverno, Michael Luck, Pablo Noriega, Juan A. Rodriguez-Aguilar, Carles Sierra | Just as conventional institutions are organisational structures for coordinating the activities of multiple interacting individuals, electronic institutions providea computational analogue for coordinating theactivities of multiple interacting software agents.In this paper, we argue that open multi-agent systemscan be effectively designed and implementedas electronic institutions, for which we provide acomprehensive computational model. |
| 454 | The CQC Algorithm: Cycling in Graphs to Semantically Enrich and Enhance a Bilingual Dictionary (Extended Abstract) | Tiziano Flati, Roberto Navigli | In this paper we present Cycles and Quasi-Cycles (CQC), a novel algorithm for the automated disambiguation of ambiguous translations in the lexical entries of a bilingual machine-readable dictionary. |
| 455 | Algorithms for Generating Ordered Solutions for Explicit AND/OR Structures: Extended Abstract | Priyankar Ghosh, Amit Sharma, P. P. Chakrabarti, Pallab Dasgupta | We present algorithms for generating alternative solutions for explicit acyclic AND/OR structures in non-decreasing order of cost. |
| 456 | YAGO2: A Spatially and Temporally Enhanced Knowledge Base from Wikipedia (Extended Abstract) | Johannes Hoffart, Fabian M. Suchanek, Klaus Berberich, Gerhard Weikum | In this paper, we present the extraction methodology and the integration of the spatio-temporal dimension. |
| 457 | Modeling Social Causality and Responsibility Judgment in Multi-Agent Interactions: Extended Abstract | Wenji Mao, Jonathan Gratch | Based on psychological attribution theory, this paper presents a domain-independent computational model to automate social causality and responsibility judgment according to an agent’s causal knowledge and observations of interaction. |
| 458 | The Extended Global Cardinality Constraint: An Empirical Survey (Extended Abstract) | Peter Nightingale | In this paper, I focus on the highest strength of inference usually considered, enforcing generalized arc consistency (GAC) on the target variables. |
| 459 | Revisiting Centrality-as-Relevance: Support Sets and Similarity as Geometric Proximity: Extended Abstract | Ricardo Ribeiro, David Martins de Matos | Thorough automatic evaluation shows that the method achieves state-of-the-art performance, both in written text, and automatically transcribed speech summarization, even when compared to considerably more complex approaches. |
| 460 | Generalized Biwords for Bitext Compression and Translation Spotting: Extended Abstract | Felipe Sánchez-Martínez, Rafael C. Carrasco, Miguel A. Martínez-Prieto, Joaquín Adiego | We therefore introduce a generalization of biwords which can describe multi-word expressions and reorderings. |
| 461 | Computing Text Semantic Relatedness Using the Contents and Links of a Hypertext Encyclopedia: Extended Abstract | Majid Yazdani, Andrei Popescu-Belis | We propose methods for computing semantic relatedness between words or texts by using knowledge from hypertext encyclopedias such as Wikipedia. |
| 462 | On the Approximation Ability of Evolutionary Optimization with Application to Minimum Set Cover: Extended Abstract | Yang Yu, Xin Yao, Zhi-Hua Zhou | In this work, we investigate a largely underexplored issue: the approximation performance of EAs in terms of how close the obtained solution is to an optimal solution. |
| 463 | Learning Qualitative Models from Numerical Data: Extended Abstract | Jure Zabkar, Martin Mozina, Ivan Bratko, Janez Demsar | We describe Padé, a new method for qualitative learning which estimates partial derivatives of the target function from training data and uses them to induce qualitative models of the target function. |
| 464 | Decision-Theoretic Approximations for Machine Learning | M. Ehsan Abbasnejad | Decision theory focuses on the problem of making decisions under uncertainty. |
| 465 | Managing Qualitative Preferences and Constraints in a Dynamic Environment | Eisa Alanazi, Malek Mouhoub | Our work aims to enhance the current literature of the problem by providing solving methods targeting the problem in a dynamic environments. |
| 466 | Towards a Deeper Understanding of Nonmonotonic Reasoning with Degrees | Marjon Blondeel, Steven Schockaert, Dirk Vermeir, Martine De Cock | Since it is a relatively new concept, little is known about the computational complexity of fuzzy answer set programming (FASP) and almost no techniques are available to compute answer sets of FASP programs. |
| 467 | Capabilities in Heterogeneous Multi Robot Systems | Jennifer Buehler | This work develops a framework that formalizes robots’ capabilities, relating to hard- and software configurations and providing a means to estimate a robot’s suitability for a task. |
| 468 | Negotiation Algorithms for Large Agreement Spaces | Dave de Jonge | We introduce a new family negotiation algorithms for complex domains with a large space of possible solutions, non-linear utility functions, limited time and many agents. |
| 469 | Trust Modeling for Opinion Evaluation by Coping with Subjectivity and Dishonesty | Hui Fang | Trust Modeling for Opinion Evaluation by Coping with Subjectivity and Dishonesty |
| 470 | High-Level Program Execution in Multi-Agent Settings | Liangda Fang | In this paper, we state the challenges of high-level program execution in multi-agent settings. |
| 471 | Using Domain Knowledge to Systematically Guide Feature Selection | William Groves | In this work, we propose leveraging known relationships between variables to constrain and guide feature selection. |
| 472 | Improving the Performance of Recommender Systems by Alleviating the Data Sparsity and Cold Start Problems | Guibing Guo | In this research, we present two different solutions to ameliorate these issues. |
| 473 | Strategic Interactions among Agents with Bounded Rationality | Pablo Hernandez-Leal, Enrique Munoz de Cote, L. Enrique Sucar | The objective of my work will be to develop a framework for learning agent models (opponent or teammate) more accurately and with less interactions, with a special focus on fast learning non-stationary strategies. |
| 474 | Problem Transformations and Algorithm Selection for CSPs | Barry Hurley, Barry O’Sullivan | Problem Transformations and Algorithm Selection for CSPs |
| 475 | Rolling Dispersion and Exploration for Robot Teams | Elizabeth A. Jensen | We have developed an algorithm to allow a small group of robots to progressively explore an unknown environment, moving as a group until full exploration is achieved. |
| 476 | Towards the Design of Robust Trust and Reputation Systems | Siwei Jiang | In this paper, we propose two approaches to deal with unfair rating attacks. |
| 477 | Maintaining Soft Arc Consistencies in BnB-ADOPT+ during Search | Ka Man Lei | Here we introduce methods to maintain soft arc consistencies in every subproblem during search. |
| 478 | Concept Generation in Language Evolution | Martha Lewis, Jonathan Lawry | We give a method for combining concepts, and will be investigating the utility of composite concepts in language evolution and thence the utility of concept generation. |
| 479 | Normative Conflict Detection and Resolution in Cooperating Institutions | Tingting Li | In this thesis, we aim: (i) to identify the different ways to combine institutions, (ii) to model those ways formally and computationally by extending an existing model for single institutions, (iii) to detect conflicts in different types of combined institutions automatically, and (iv) to resolve those conflicts via automatic norm revision using an approach based on inductive learning. |
| 480 | Dynamic of Argumentation Frameworks | Jean-Guy Mailly | My thesis work aims to study change operations for argumentation systems, especially for abstract argumentation systems à la Dung. |
| 481 | Approximation Algorithms for Max-Sum-Product Problems | Denis Deratani Mauá | We describe our results in obtaining a new approximation scheme for the problem, that can be turned into an anytime procedure. |
| 482 | On Teaching Collaboration to a Team of Autonomous Agents via Imitation | Saleha Raza | This research proposes the use of imitation based learning to build collaborative strategies for a team of agents. |
| 483 | Semi-Supervised Structuring of Complex Data | Marian-Andrei Rizoiu | The objective of the thesis is to explore how complex data can be treated using unsupervised machine learning techniques, in which additional information is injected to guide the exploratory process. |
| 484 | Object Recognition Based on Visual Grammars and Bayesian Networks | Elías Ruiz, L. Enrique Sucar | Object Recognition Based on Visual Grammars and Bayesian Networks |
| 485 | Adapting Surface Sketch Recognition Techniques for Surfaceless Sketches | Paul Taele, Tracy Anne Hammond | Researchers have made significant strides in developing recognition techniques for surface sketches, with realized and potential applications to motivate extending these techniques towards analogous surfaceless sketches. |
| 486 | Ontology Based Query Answering with Existential Rules | Michaël Thomazo | The aim of my Ph.D thesis is to identify expressive decidable classes, study the complexity of reasoning for these classes, and design efficient algorithms in the sense that they improve state of the art algorithms. |
| 487 | Behavior Composition Optimization | Nitin Yadav | In this doctoral work, we look at quantitative and qualitative ways to address this question. |
| 488 | Incorporating Expert Judgement into Bayesian Network Machine Learning | Yun Zhou, Norman Fenton, Martin Neil, Cheng Zhu | We review the challenges of Bayesian network learning, especially parameter learning, and specify the problem of learning with sparse data. |
| 489 | Arbitration and Stability in Cooperative Games with Overlapping Coalitions | Yair Zick | In this thesis, we study stability in OCF games. |