Most Influential IJCAI Papers

March 8, 2021May 4, 2021 admin

International Joint Conference on Artificial Intelligence (IJCAI) is one of the top artificial intelligence conferences in the world. Paper Digest Team analyze all papers published on IJCAI in the past years, and presents the 15 most influential papers for each year. This ranking list is automatically constructed based upon citations from both research papers and granted patents, and will be frequently updated to reflect the most recent changes. To find the most influential papers from other conferences/journals, visit Best Paper Digest page. Note: the most influential papers may or may not include the papers that won the best paper awards. (Version: 2021-03)

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. To search for papers with highlights, related papers, patents, grants, experts and organizations, please visit our search console. 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: Most Influential IJCAI Papers

Year	Rank	Paper	Author(s)
2020	1	Closing The Generalization Gap Of Adaptive Gradient Methods In Training Deep Neural Networks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show that adaptive gradient methods such as Adam, Amsgrad, are sometimes "over adapted".	JINGHUI CHEN et. al.
2020	2	Transformers As Soft Reasoners Over Language IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper investigates a modern approach to this problem where the facts and rules are provided as natural language sentences, thus bypassing a formal representation.	Peter Clark; Oyvind Tafjord; Kyle Richardson;
2020	3	GraphFlow: Exploiting Conversation Flow With Graph Neural Networks For Conversational Machine Comprehension IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we first propose a simple yet effective graph structure learning technique to dynamically construct a question and conversation history aware context graph at each conversation turn. Then we propose a novel Recurrent Graph Neural Network, and based on that, we introduce a flow mechanism to model the temporal dependencies in a sequence of context graphs.	Yu Chen; Lingfei Wu; Mohammed J. Zaki;
2020	4	Diffusion Variational Autoencoders IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To remove topological obstructions, we introduce Diffusion Variational Autoencoders (DeltaVAE) with arbitrary (closed) manifolds as a latent space.	Luis A. Perez Rey; Vlado Menkovski; Jim Portegies;
2020	5	FakeSpotter: A Simple Yet Robust Baseline For Spotting AI-Synthesized Fake Faces IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a novel approach, named FakeSpotter, based on monitoring neuron behaviors to spot AI-synthesized fake faces.	RUN WANG et. al.
2020	6	AdaBERT: Task-Adaptive BERT Compression With Differentiable Neural Architecture Search IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by the necessity and benefits of task-oriented BERT compression, we propose a novel compression method, AdaBERT, that leverages differentiable Neural Architecture Search to automatically compress BERT into task-adaptive small models for specific tasks.	DAOYUAN CHEN et. al.
2020	7	A Survey On Computational Propaganda Detection IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts between these communities.	GIOVANNI DA SAN MARTINO et. al.
2020	8	Channel Pruning Via Automatic Structure Search IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new channel pruning method based on artificial bee colony algorithm (ABC), dubbed as ABCPruner, which aims to efficiently find optimal pruned structure, i.e., channel number in each layer, rather than selecting "important" channels as previous works did.	MINGBAO LIN et. al.
2020	9	Automatic Curriculum Learning For Deep RL: A Short Survey IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The ambition of this work is dual: 1) to present a compact and accessible introduction to the Automatic Curriculum Learning literature and 2) to draw a bigger picture of the current state of the art in ACL to encourage the cross-breeding of existing concepts and the emergence of new ideas.	Rémy Portelas; Cédric Colas; Lilian Weng; Katja Hofmann; Pierre-Yves Oudeyer;
2020	10	Maximum Nash Welfare And Other Stories About EFX IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider the classic problem of fairly allocating indivisible goods among agents with additive valuation functions and explore the connection between two prominent fairness notions: maximum Nash welfare (MNW) and envy-freeness up to any good (EFX).	Georgios Amanatidis; Georgios Birmpas; Aris Filos-Ratsikas; Alexandros Hollender; Alexandros A. Voudouris;
2020	11	Graph Neural Networks Meet Neural-Symbolic Computing: A Survey And Perspective IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we review the state-of-the-art on the use of GNNs as a model of neural-symbolic computing.	LU&IACUTE;S C. LAMB et. al.
2020	12	Maximizing Welfare With Incentive-Aware Evaluation Mechanisms IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by applications such as college admission and insurance rate determination, we study a classification problem where the inputs are controlled by strategic individuals who can modify their features at a cost.	Nika Haghtalab; Nicole Immorlica; Brendan Lucier; Jack Z. Wang;
2020	13	TRP: Trained Rank Pruning For Efficient Deep Neural Networks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Trained Rank Pruning (TRP), which alternates between low rank approximation and training.	YUHUI XU et. al.
2020	14	Heterogeneous Network Representation Learning IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this survey, we examine and review the problem of representation learning with the focus on heterogeneous networks, which consists of different types of vertices and relations.	Yuxiao Dong; Ziniu Hu; Kuansan Wang; Yizhou Sun; Jie Tang;
2020	15	Smart Voting IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a generalisation of liquid democracy in which a voter can either vote directly on the issues at stake, delegate her vote to another voter, or express complex delegations to a set of trusted voters.	Rachael Colley; Umberto Grandi; Arianna Novaro;
2019	1	Interpolation Consistency Training For Semi-supervised Learning IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce Interpolation Consistency Training (ICT), a simple and computation efficient algorithm for training Deep Neural Networks in the semi-supervised learning paradigm.	Vikas Verma; Alex Lamb; Juho Kannala; Yoshua Bengio; David Lopez-Paz;
2019	2	Graph WaveNet For Deep Spatial-Temporal Graph Modeling IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome these limitations, we propose in this paper a novel graph neural network architecture, {Graph WaveNet}, for spatial-temporal graph modeling.	Zonghan Wu; Shirui Pan; Guodong Long; Jing Jiang; Chengqi Zhang;
2019	3	Topology Attack And Defense For Graph Neural Networks: An Optimization Perspective IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Moreover, leveraging our gradient-based attack, we propose the first optimization-based adversarial training for GNNs.	KAIDI XU et. al.
2019	4	Obstacle Tower: A Generalization Challenge In Vision, Control, And Planning IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we outline the environment and provide a set of baseline results produced by current state-of-the-art Deep RL methods as well as human players.	ARTHUR JULIANI et. al.
2019	5	Robust Audio Adversarial Example For A Physical Attack IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method to generate audio adversarial examples that can attack a state-of-the-art speech recognition model in the physical world.	Hiromu Yakura; Jun Sakuma;
2019	6	Adversarial Examples For Graph Data: Deep Insights Into Attack And Defense IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose techniques for both an adversarial attack and a defense against adversarial attacks.	HUIJUN WU et. al.
2019	7	Multi-view Knowledge Graph Embedding For Entity Alignment IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel framework that unifies multiple views of entities to learn embeddings for entity alignment.	QINGHENG ZHANG et. al.
2019	8	ANODE: Unconditionally Accurate Memory-Efficient Gradients For Neural ODEs IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We discuss the underlying problems, and to address them we propose ANODE, a neural ODE framework which avoids the numerical instability related problems noted above.	Amir Gholaminejad; Kurt Keutzer; George Biros;
2019	9	DeepInspect: A Black-box Trojan Detection And Mitigation Framework For Deep Neural Networks IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our goal in this paper is to address the security concern on unknown DNN to NT attacks and ensure safe model deployment.	Huili Chen; Cheng Fu; Jishen Zhao; Farinaz Koushanfar;
2019	10	Deep Session Interest Network For Click-Through Rate Prediction IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on this observation, we propose a novel CTR model named Deep Session Interest Network (DSIN) that leverages users’ multiple historical sessions in their behavior sequences.	YUFEI FENG et. al.
2019	11	Talking Face Generation By Conditional Recurrent Adversarial Network IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel conditional recurrent generation network that incorporates both image and audio features in the recurrent unit for temporal dependency.	Yang Song; Jingwen Zhu; Dawei Li; Andy Wang; Hairong Qi;
2019	12	A Dual Reinforcement Learning Framework For Unsupervised Text Style Transfer IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Therefore, in this paper, we propose a dual reinforcement learning framework to directly transfer the style of the text via a one-step mapping model, without any separation of content and style.	FULI LUO et. al.
2019	13	Learning To Select Knowledge For Response Generation In Dialog Systems IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Motivated by this, we propose an end-to-end neural model which employs a novel knowledge selection mechanism where both prior and posterior distributions over knowledge are used to facilitate knowledge selection.	Rongzhong Lian; Min Xie; Fan Wang; Jinhua Peng; Hua Wu;
2019	14	Transferable Adversarial Attacks For Image And Video Object Detection IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address these issues, we present a generative method to obtain adversarial images and videos, thereby significantly reducing the processing time.	Xingxing Wei; Siyuan Liang; Ning Chen; Xiaochun Cao;
2019	15	Relation-Aware Entity Alignment For Heterogeneous Knowledge Graphs IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel Relation-aware Dual-Graph Convolutional Network (RDGCN) to incorporate relation information via attentive interactions between the knowledge graph and its dual relation counterpart, and further capture neighboring structures to learn better entity representations.	YUTING WU et. al.
2018	1	Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework For Traffic Forecasting IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel deep learning framework, Spatio-Temporal Graph Convolutional Networks (STGCN), to tackle the time series prediction problem in traffic domain.	Bing Yu; Haoteng Yin; Zhanxing Zhu;
2018	2	Soft Filter Pruning For Accelerating Deep Convolutional Neural Networks IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper proposed a Soft Filter Pruning (SFP) method to accelerate the inference procedure of deep Convolutional Neural Networks (CNNs).	Yang He; Guoliang Kang; Xuanyi Dong; Yanwei Fu; Yi Yang;
2018	3	Generating Adversarial Examples With Adversarial Networks IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose AdvGAN to generate adversarial exam- ples with generative adversarial networks (GANs), which can learn and approximate the distribution of original instances.	CHAOWEI XIAO et. al.
2018	4	A Genetic Programming Approach To Designing Convolutional Neural Network Architectures IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method for designing convolutional neural network (CNN) architectures based on Cartesian genetic programming (CGP).	Masanori Suganuma; Shinichi Shirakawa; Tomoharu Nagao;
2018	5	Commonsense Knowledge Aware Conversation Generation With Graph Attention IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel open-domain conversation generation model to demonstrate how large-scale commonsense knowledge can facilitate language understanding and generation.	HAO ZHOU et. al.
2018	6	Deep Text Classification Can Be Fooled IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present an effective method to craft text adversarial samples, revealing one important yet underestimated fact that DNN-based text classifiers are also prone to adversarial sample attack.	BIN LIANG et. al.
2018	7	Adversarially Regularized Graph Autoencoder For Graph Embedding IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel adversarial graph embedding framework for graph data.	SHIRUI PAN et. al.
2018	8	Reinforced Mnemonic Reader For Machine Reading Comprehension IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce the Reinforced Mnemonic Reader for machine reading comprehension tasks, which enhances previous attentive readers in two aspects.	MINGHAO HU et. al.
2018	9	Behavioral Cloning From Observation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a two-phase, autonomous imitation learning technique called behavioral cloning from observation (BCO), that aims to provide improved performance with respect to both of these aspects.	Faraz Torabi; Garrett Warnell; Peter Stone;
2018	10	Enhanced-alignment Measure For Binary Foreground Map Evaluation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we take a detailed look at current binary FM evaluation measures and propose a novel and effective E-measure (Enhanced-alignment measure).	DENG-PING FAN et. al.
2018	11	Unbiased Learning-to-Rank With Biased Feedback IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To overcome this bias problem, we present a counterfactual inference framework that provides the theoretical basis for unbiased LTR via Empirical Risk Minimization despite biased data.	Thorsten Joachims; Adith Swaminathan; Tobias Schnabel;
2018	12	R³Net: Recurrent Residual Refinement Network For Saliency Detection IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel recurrent residual refinement network (R^3Net) equipped with residual refinement blocks (RRBs) to more accurately detect salient regions of an input image.	ZIJUN DENG et. al.
2018	13	Outer Product-based Neural Collaborative Filtering IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we contribute a new multi-layer neural network architecture named ONCF to perform collaborative filtering.	XIANGNAN HE et. al.
2018	14	Co-occurrence Feature Learning From Skeleton Data For Action Recognition And Detection With Hierarchical Aggregation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose an end-to-end convolutional co-occurrence feature learning framework.	Chao Li; Qiaoyong Zhong; Di Xie; Shiliang Pu;
2018	15	Ontology-Based Data Access: A Survey IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present the framework of ontology-based data access, a semantic paradigm for providing a convenient and user-friendly access to data repositories, which has been actively developed and studied in the past decade.	GUOHUI XIAO et. al.
2017	1	DeepFM: A Factorization-Machine Based Neural Network For CTR Prediction IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that it is possible to derive an end-to-end learning model that emphasizes both low- and high-order feature interactions.	Huifeng Guo; Ruiming TANG; Yunming Ye; Zhenguo Li; Xiuqiang He;
2017	2	Bilateral Multi-Perspective Matching For Natural Language Sentences IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a bilateral multi-perspective matching (BiMPM) model.	Zhiguo Wang; Wael Hamza; Radu Florian;
2017	3	Deep Forest: Towards An Alternative To Deep Neural Networks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose gcForest, a decision tree ensemble approach with performance highly competitive to deep neural networks in a broad range of tasks.	Zhi-Hua Zhou; Ji Feng;
2017	4	Value Iteration Networks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce the value iteration network (VIN): a fully differentiable neural network with a `planning module’ embedded within.	Aviv Tamar; Yi Wu; Garrett Thomas; Sergey Levine; Pieter Abbeel;
2017	5	Interactive Attention Networks For Aspect-Level Sentiment Classification IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we argue that both targets and contexts deserve special treatment and need to be learned their own representations via interactive learning.	Dehong Ma; Sujian Li; Xiaodong Zhang; Houfeng Wang;
2017	6	Person Re-Identification By Deep Joint Learning Of Multi-Loss Classification IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we show the advantages of jointly learning local and global features in a Convolutional Neural Network (CNN) by aiming to discover correlated local and global features in different context.	Wei Li; Xiatian Zhu; Shaogang Gong;
2017	7	A Dual-Stage Attention-Based Recurrent Neural Network For Time Series Prediction IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a dual-stage attention-based recurrent neural network (DA-RNN) to address these two issues.	YAO QIN et. al.
2017	8	Attentional Factorization Machines: Learning The Weight Of Feature Interactions Via Attention Networks IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we improve FM by discriminating the importance of different feature interactions.	JUN XIAO et. al.
2017	9	Demystifying Neural Style Transfer IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel interpretation of neural style transfer by treating it as a domain adaptation problem.	Yanghao Li; Naiyan Wang; Jiaying Liu; Xiaodi Hou;
2017	10	Deep Matrix Factorization Models For Recommender Systems IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel matrix factorization model with neural network architecture.	Hong-Jian Xue; Xinyu Dai; Jianbing Zhang; Shujian Huang; Jiajun Chen;
2017	11	Variational Deep Embedding: An Unsupervised And Generative Approach To Clustering IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose Variational Deep Embedding (VaDE), a novel unsupervised generative clustering approach within the framework of Variational Auto-Encoder (VAE).	Zhuxi Jiang; Yin Zheng; Huachun Tan; Bangsheng Tang; Hanning Zhou;
2017	12	Right For The Right Reasons: Training Differentiable Models By Constraining Their Explanations IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a method to explain the predictions of any differentiable model via the gradient of the class label with respect to the input (which provides a normal to the decision boundary).	Andrew Slavin Ross; Michael C. Hughes; Finale Doshi-Velez;
2017	13	Improved Deep Embedded Clustering With Local Structure Preservation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this issue, in this paper, we propose the Improved Deep Embedded Clustering (IDEC) algorithm to take care of data structure preservation.	Xifeng Guo; Long Gao; Xinwang Liu; Jianping Yin;
2017	14	Combining Knowledge With Deep Convolutional Neural Networks For Short Text Classification IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a framework based on convolutional neural networks that combines explicit and implicit representations of short text for classification.	Jin Wang; Zhongyuan Wang; Dawei Zhang; Jun Yan;
2017	15	Plan Explanations As Model Reconciliation: Moving Beyond Explanation As Soliloquy IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In particular, we show how explanation can be seen as a model reconciliation problem (MRP), where the AI system in effect suggests changes to the human’s model, so as to make its plan be optimal with respect to that changed human model.	Tathagata Chakraborti; Sarath Sreedharan; Yu Zhang; Subbarao Kambhampati;
2016	1	Recurrent Neural Network For Text Classification With Multi-Task Learning IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we use the multi-task learning framework to jointly learn across multiple related tasks.	Pengfei Liu; Xipeng Qiu; Xuanjing Huang;
2016	2	Deep, Convolutional, And Recurrent Models For Human Activity Recognition Using Wearables IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we rigorously explore deep, convolutional, and recurrent approaches across three representative datasets that contain movement data captured with wearable sensors.	Nils Y. Hammerla; Shane Halloran; Thomas Plötz;
2016	3	Feature Learning Based Deep Supervised Hashing With Pairwise Labels IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel deep hashing method, called deep pairwise-supervised hashing (DPSH), to perform simultaneous feature learning and hash-code learning for applications with pairwise labels.	Wu-Jun Li; Sheng Wang; Wang-Cheng Kang;
2016	4	Detecting Rumors From Microblogs With Recurrent Neural Networks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents a novel method that learns continuous representations of microblog events for identifying rumors.	JING MA et. al.
2016	5	Deep Neural Decision Forests IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel approach to enrich classification trees with the representation learning ability of deep (neural) networks within an end-to-end trainable architecture.	Peter Kontschieder; Madalina Fiterau; Antonio Criminisi; Samuel Rota Bulò;
2016	6	Tri-Party Deep Network Representation IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose TriDNR, a tri-party deep network representation model, using information from three parties: node structure, node content, and node labels (if available) to jointly learn optimal node representation.	Shirui Pan; Jia Wu; Xingquan Zhu; Chengqi Zhang; Yang Wang;
2016	7	The Malmo Platform For Artificial Intelligence Experimentation IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present Project Malmo – an AI experimentation platform built on top of the popular computer game Minecraft, and designed to support fundamental research in artificial intelligence.	Matthew Johnson; Katja Hofmann; Tim Hutton; David Bignell;
2016	8	Max-Margin DeepWalk: Discriminative Learning Of Network Representation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we overcome this challenge by proposing a novel semi-supervised model, max-margin DeepWalk (MMDW).	Cunchao Tu; Weicheng Zhang; Zhiyuan Liu; Maosong Sun;
2016	9	Urban Water Quality Prediction Based On Multi-Task Multi-View Learning IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we forecast the water quality of a station over the next few hours, using a multi-task multi-view learning method to fuse multiple datasets from different domains.	Ye Liu; Yu Zheng; Yuxuan Liang; Shuming Liu; David S. Rosenblum;
2016	10	Parameter-Free Auto-Weighted Multiple Graph Learning: A Framework For Multiview Clustering And Semi-Supervised Classification IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the real-world applications where the same instance can be represented by multiple heterogeneous features.	Feiping Nie; Jing Li; Xuelong Li;
2016	11	Neural Generative Question Answering IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper presents an end-to-end neural network model, named Neural Generative Question Answering (GENQA), that can generate answers to simple factoid questions, based on the facts in a knowledge-base.	JUN YIN et. al.
2016	12	Model-Based Deep Hand Pose Estimation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work, we propose a model based deep learning approach that adopts a forward kinematics based layer to ensure the geometric validity of estimated poses.	Xingyi Zhou; Qingfu Wan; Wei Zhang; Xiangyang Xue; Yichen Wei;
2016	13	Staleness-Aware Async-SGD For Distributed Deep Learning IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a variant of the ASGD algorithm in which the learning rate is modulated according to the gradient staleness and provide theoretical guarantees for convergence of this algorithm.	Wei Zhang; Suyog Gupta; Xiangru Lian; Ji Liu;
2016	14	A Joint Model Of Intent Determination And Slot Filling For Spoken Language Understanding IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on the idea that the intent and semantic slots of a sentence are correlative, we propose a joint model for both tasks.	Xiaodong Zhang; Houfeng Wang;
2016	15	Iterative Views Agreement: An Iterative Low-Rank Based Structured Optimization Method To Multi-View Spectral Clustering IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, 1) we propose a multi-graph laplacian regularized LRR with each graph laplacian corresponding to one view to characterize its local manifold structure.	YANG WANG et. al.
2015	1	The Arcade Learning Environment: An Evaluation Platform For General Agents (Extended Abstract) IF:8 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this extended abstract we introduce the Arcade Learning Environment (ALE): both a challenge problem and a platform and methodology for evaluating the development of general, domain-independent AI technology.	Marc Bellemare; Yavar Naddaf; Joel Veness; Michael Bowling;
2015	2	Framing Image Description As A Ranking Task: Data, Models And Evaluation Metrics (Extended Abstract) IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new dataset of images paired with multiple descriptive captions that was specifically designed for these tasks.	Micah Hodosh; Peter Young; Julia Hockenmaier;
2015	3	Deep Convolutional Neural Networks On Multichannel Time Series For Human Activity Recognition IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a systematic feature learning method for HAR problem.	Jianbo Yang; Minh Nhut Nguyen; Phyo Phyo San; Xiao Li Li; Shonali Krishnaswamy;
2015	4	Network Representation Learning With Rich Text Information IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: By proving that DeepWalk, a state-of-the-art network representation method, is actually equivalent to matrix factorization (MF), we propose text-associated DeepWalk (TADW).	Cheng Yang; Zhiyuan Liu; Deli Zhao; Maosong Sun; Edward Chang;
2015	5	Deep Learning For Event-Driven Stock Prediction IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a deep learning method for event-driven stock market prediction.	Xiao Ding; Yue Zhang; Ting Liu; Junwen Duan;
2015	6	Action2Activity: Recognizing Complex Activities From Sensor Data IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To this end, this paper presents a novel approach for complex activity recognition comprising of two components.	Ye Liu; Liqiang Nie; Lei Han; Luming Zhang; David S. Rosenblum;
2015	7	Speeding Up Automatic Hyperparameter Optimization Of Deep Neural Networks By Extrapolation Of Learning Curves IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Automated hyperparameter optimization methods have recently been shown to yield settings competitive with those found by human experts, but their widespread adoption is hampered by the fact that they require more computational resources than human experts.	Tobias Domhan; Jost Tobias Springenberg; Frank Hutter;
2015	8	Personalized Ranking Metric Embedding For Next New POI Recommendation IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a personalized ranking metric embedding method (PRME) to model personalized check-in sequences.	SHANSHAN FENG et. al.
2015	9	Target-Dependent Twitter Sentiment Classification With Rich Automatic Features IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we show that competitive results can be achieved without the use of syntax, by extracting a rich set of automatic features.	Tin Duy Vo; Yue Zhang;
2015	10	Convolutional Neural Tensor Network Architecture For Community-Based Question Answering IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a convolutional neural tensor network architecture to encode the sentences in semantic space and model their interactions with a tensor layer.	Xipeng Qiu; Xuanjing Huang;
2015	11	Joint Learning Of Character And Word Embeddings IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence, we take Chinese for example, and present a character-enhanced word embedding model (CWE).	Xinxiong Chen; Lei Xu; Zhiyuan Liu; Maosong Sun; Huanbo Luan;
2015	12	Supervised Representation Learning: Transfer Learning With Deep Autoencoders IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a supervised representation learning method based on deep autoencoders for transfer learning.	Fuzhen Zhuang; Xiaohu Cheng; Ping Luo; Sinno Jialin Pan; Qing He;
2015	13	Self-Adaptive Hierarchical Sentence Model IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As an effort towards this goal we propose a self-adaptive hierarchical sentence model (AdaSent).	Han Zhao; Zhengdong Lu; Pascal Poupart;
2015	14	Scalable Graph Hashing With Feature Transformation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel method, called scalable graph hashing with feature transformation (SGH), for large-scale graph hashing.	Qing-Yuan Jiang; Wu-Jun Li;
2015	15	Modeling Mention, Context And Entity With Neural Networks For Entity Disambiguation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Given a query consisting of a mention (name string) and a background document,entity disambiguation calls for linking the mention to an entity from reference knowledge base like Wikipedia.Existing studies typically use hand-crafted features to represent mention, context and entity, which is labor-intensive and weak to discover explanatory factors of data.In this paper, we address this problem by presenting a new neural network approach.The model takes consideration of the semantic representations of mention, context and entity, encodes them in continuous vector space and effectively leverages them for entity disambiguation.Specifically, we model variable-sized contexts with convolutional neural network, and embed the positions of context words to factor in the distance between context word and mention.Furthermore, we employ neural tensor network to model the semantic interactions between context and mention.We conduct experiments for entity disambiguation on two benchmark datasets from TAC-KBP 2009 and 2010.	YAMING SUN et. al.
2013	1	Human Action Recognition Using A Temporal Hierarchy Of Covariance Descriptors On 3D Joint Locations IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a novel approach to human action recognition from 3D skeleton sequences extracted from depth data.	Mohamed E. Hussein; Marwan Torki; Mohammad A. Gowayyed; Motaz El-Saban;
2013	2	Where You Like To Go Next: Successive Point-of-Interest Recommendation IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Chen Cheng; Haiqin Yang; Michael R. Lyu; Irwin King;
2013	3	Multi-View K-Means Clustering On Big Data IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new robust large-scale multi-view clustering method to integrate heterogeneous representations of large-scale data.	Xiao Cai; Feiping Nie; Heng Huang;
2013	4	Social Collaborative Filtering By Trust IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Bo Yang; Yu Lei; Dayou Liu; Jiming Liu;
2013	5	Linear Temporal Logic And Linear Dynamic Logic On Finite Traces IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we look into the assumption of interpreting LTL over finite traces.	Giuseppe De Giacomo; Moshe Y. Vardi;
2013	6	Learning Discriminative Representations From RGB-D Video Data IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Li Liu; Ling Shao;
2013	7	Bayesian Optimization In High Dimensions Via Random Embeddings IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel random embedding idea to attack this problem.	Ziyu Wang; Masrour Zoghi; Frank Hutter; David Matheson; Nando de Freitas;
2013	8	Exact Recovery Of Sparsely-Used Dictionaries IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We consider the problem of learning sparsely used dictionaries with an arbitrary square dictionary and a random, sparse coefficient matrix.	Daniel A. Spielman; Huan Wang; John Wright;
2013	9	Social Influence Locality For Modeling Retweeting Behaviors IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Jing Zhang; Biao Liu; Jie Tang; Ting Chen; Juanzi Li;
2013	10	Robust Unsupervised Feature Selection IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A new unsupervised feature selection method, i.e., Robust Unsupervised Feature Selection (RUFS), is proposed.	Mingjie Qian; Chengxiang Zhai;
2013	11	Histogram Of Oriented Displacements (HOD): Describing Trajectories Of Human Joints For Action Recognition IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Here, we propose a novel descriptor for 2D trajectories: Histogram of Oriented Displacements (HOD).	Mohammad A. Gowayyed; Marwan Torki; Mohamed E. Hussein; Motaz El-Saban;
2013	12	A Novel Bayesian Similarity Measure For Recommender Systems IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Guibing Guo; Jie Zhang; Neil Yorke-Smith;
2013	13	GBPR: Group Preference Based Bayesian Personalized Ranking For One-Class Collaborative Filtering IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: As a response, we propose a new and improved assumption, group Bayesian personalized ranking (GBPR), via introducing richer interactions among users.	Weike Pan; Li Chen;
2013	14	Exploiting Local And Global Social Context For Recommendation IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: 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.	Jiliang Tang; Xia Hu; Huiji Gao; Huan Liu;
2013	15	Abstract Dialectical Frameworks Revisited IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present various new concepts and results related to abstract dialectical frameworks (ADFs), a powerful generalization of Dung’s argumentation frameworks (AFs).	Gerhard Brewka; Stefan Ellmauthaler; Hannes Strass; Johannes Peter Wallner; Stefan Woltran;
2011	1	Flexible, High Performance Convolutional Neural Networks For Image Classification IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a fast, fully parameterizable GPU implementation of Convolutional Neural Network variants.	Dan C. Ciresan; Ueli Meier; Jonathan Masci; Luca Maria Gambardella; Jürgen Schmidhuber;
2011	2	WSABIE: Scaling Up To Large Vocabulary Image Annotation IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a strongly performing method that scales to such datasets by simultaneously learning to optimize precision at the top of the ranked list of annotations for a given image and learning a low-dimensional joint embedding space for both images and annotations.	Jason Weston; Samy Bengio; Nicolas Usunier;
2011	3	Open Information Extraction: The Second Generation IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In 2007, we introduced the Open Information Extraction (Open IE) paradigm which eschews handlabeled training examples, and avoids domain-specific verbs and nouns, to develop unlexicalized, domain-independent extractors that scale to the Web corpus.	Oren Etzioni; Anthony Fader; Janara Christensen; Stephen Soderland; Mausam;
2011	4	Learning Hash Functions For Cross-View Similarity Search IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we consider the problem of learning hash functions for similarity search across the views for such applications.	Shaishav Kumar; Raghavendra Udupa;
2011	5	Learning To Identify Review Spam IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study this issue in the context of our product review mining system.	Fangtao Li; Minlie Huang; Yi Yang; Xiaoyan Zhu;
2011	6	Heterogeneous Domain Adaptation Using Manifold Alignment IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a manifold alignment based approach for heterogeneous domain adaptation.	Chang Wang; Sridhar Mahadevan;
2011	7	Feature Learning For Activity Recognition In Ubiquitous Computing IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We investigate the potential of recent machine learning methods for discovering universal features for context-aware applications of activity recognition.	Thomas Plötz; Nils Y. Hammerla; Patrick Olivier;
2011	8	Short Text Conceptualization Using A Probabilistic Knowledgebase IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We enhance machine learning algorithms by first giving the machine a probabilistic knowledgebase that contains as big, rich, and consistent concepts (of worldly facts) as those in our mental world.	Yangqiu Song; Haixun Wang; Zhongyuan Wang; Hongsong Li; Weizhu Chen;
2011	9	SDD: A New Canonical Representation Of Propositional Knowledge Bases IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We identify a new representation of propositional knowledge bases, the Sentential Decision Diagram SDD, which is interesting for a number of reasons.	Adnan Darwiche;
2011	10	LIFT: Multi-Label Learning With Label-Specific Features IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Based on the above reflection, we propose a new strategy to multi-label learning by leveraging label-specific features, where a simple yet effective algorithm named LIFT is presented.	Min-Ling Zhang;
2011	11	Short Text Classification Improved By Learning Multi-Granularity Topics IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we move forward along this direction by proposing an method to leverage topics at multiple granularity, which can model the short text more precisely.	Mengen Chen; Xiaoming Jin; Dou Shen;
2011	12	Robust Principal Component Analysis With Non-Greedy L1-Norm Maximization IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: A recent work proposed principal component analysis based on 1-norm maximization, which is efficient and robust to outliers.	l;
2011	13	Budgeted Social Choice: From Consensus To Personalized Decision Making IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We develop a general framework for social choice problems in which a limited number of alternatives can be recommended to an agent population.	Tyler Lu; Craig Boutilier;
2011	14	Joint Feature Selection And Subspace Learning IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a framework for joint feature selection and subspace learning.	Quanquan Gu; Zhenhui Li; Jiawei Han;
2011	15	The Increasing Cost Tree Search For Optimal Multi-Agent Pathfinding IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel formalization for this problem which includes a search tree called the increasing cost tree (ICT) and a corresponding search algorithm that finds optimal solutions.	Guni Sharon; Roni Stern; Meir Goldenberg; Ariel Felner;
2009	1	Domain Adaptation Via Transfer Component Analysis IF:9 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose to find such a representation through a new learning method, transfer component analysis (TCA), for domain adaptation.	Sinno Jialin Pan; Ivor W. Tsang; James T. Kwok; Qiang Yang;
2009	2	Predicting Learnt Clauses Quality In Modern SAT Solvers IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We report in this work a key observation of CDCL solvers behavior on this family of benchmarks and explain it by an unsuspected side effect of their particular Clause Learning scheme.	Gilles Audemard; Laurent Simon;
2009	3	Expanding Domain Sentiment Lexicon Through Double Propagation IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a novel propagation approach that exploits the relations between sentiment words and topics or product features that the sentiment words modify, and also sentiment words and product features themselves to extract new sentiment words.	Guang Qiu; Bing Liu; Jiajun Bu; Chun Chen;
2009	4	Can Movies And Books Collaborate? Cross-Domain Collaborative Filtering For Sparsity Reduction IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider a novel approach for alleviating the sparsity problem in CF by transferring user-item rating patterns from a dense auxiliary rating matrix in other domains (e.g., a popular movie rating website) to a sparse rating matrix in a target domain (e.g., a new book rating website).	Bin Li; Qiang Yang; Xiangyang Xue;
2009	5	Discriminative Semi-Supervised Feature Selection Via Manifold Regularization IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: To address this problem, we propose a novel discriminative semi-supervised feature selection method based on the idea of manifold regularization.	Zenglin Xu; Rong Jin; Michael R. Lyu; Irwin King;
2009	6	Sensing And Predicting The Pulse Of The City Through Shared Bicycling IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we focus on the digital footprints from one type of emerging urban infrastructure: shared bicycling systems.	Jon Edward Froehlich; Joachim Neumann; Nuria Oliver;
2009	7	Plan Recognition As Planning IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this work we aim to narrow the gap between plan recognition and planning by exploiting the powerand generality of recent planning algorithms for recognizing the set G∗ of goals G that explain a sequenceof observations given a domain theory.	Miquel Ram?rez; Hector Geffner;
2009	8	Conjunctive Query Answering In The Description Logic EL Using A Relational Database System IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Our main contribution is a novel approach to CQ answering that enables the use of standard relational database systems as the basis for query execution.	Carsten Lutz; David Toman; David Toman; Frank Wolter; Frank Wolter;
2009	9	Consequence-Driven Reasoning For Horn SHIQ Ontologies IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a novel reasoning procedure for Horn SHIQ ontologies�SHIQ ontologies that can be translated to the Horn fragment of first-order logic.	Yevgeny Kazakov;
2009	10	UCT For Tactical Assault Planning In Real-Time Strategy Games IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we investigate the use of UCT, a recent Monte-Carlo planning algorithm for this problem.	Radha-Krishna Balla; Alan Fern;
2009	11	Nested Monte-Carlo Search IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The algorithm is studied theoretically on simple abstract problems and applied successfully to three different games: Morpion Solitaire, SameGame and 16×16 Sudoku.	Tristan Cazenave;
2009	12	Manifold Alignment Without Correspondence IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we introduce a novel manifold alignment approach, which differs from semi-supervised alignment and Procrustes alignment in that it does not require predetermining correspondences.	Chang Wang; Sridhar Mahadevan;
2009	13	Cost-Optimal Planning With Landmarks IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a methodology for deriving admissible heuristic estimates for cost-optimal planning from a set of planning landmarks.	Erez Karpas; Carmel Domshlak;
2009	14	Collaboration And Shared Plans In The Open World: Studies Of Ridesharing IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present planning, optimization, and payment mechanisms that provide fair and efficient solutions to the rideshare collaboration challenge.	Ece Kamar; Eric Horvitz;
2009	15	Large-Scale Taxonomy Mapping For Restructuring And Integrating Wikipedia IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a knowledge-rich methodology for disambiguating Wikipedia categories with WordNet synsets and using this semantic information to restructure a taxonomy automatically generated from the Wikipedia system of categories.	Simone Paolo Ponzetto; Roberto Navigli;
2007	1	Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis IF:9 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose Explicit Semantic Analysis (ESA), a novel method that represents the meaning of texts in a high-dimensional space of concepts derived from Wikipedia.	Evgeniy Gabrilovich; Shaul Markovitch;
2007	2	Open Information Extraction From The Web IF:9 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: This paper introduces Open IE (OIE), a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tuples without requiring any human input.	Michele Banko; Michael J Cafarella; Stephen Soderland; Matt Broadhead; Oren Etzioni;
2007	3	ProbLog: A Probabilistic Prolog And Its Application In Link Discovery IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: The key contribution of this paper is the introduction of an effective solver for computing success probabilities.	Luc De Raedt; Angelika Kimmig; Hannu Toivonen;
2007	4	WiFi-SLAM Using Gaussian Process Latent Variable Models IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we propose a novel technique for solving the WiFi SLAM problem using the Gaussian Process Latent Variable Model (GP-LVM) to determine the latent-space locations of unlabeled signal strength data.	Brian Ferris; Dieter Fox; Neil Lawrence;
2007	5	Bayesian Inverse Reinforcement Learning IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present efficient algorithms that find solutions for the reward learning and apprenticeship learning tasks that generalize well over these distributions.	Deepak Ramachandran; Eyal Amir;
2007	6	Locality Sensitive Discriminant Analysis IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we introduce a novel linear algorithm for discriminant analysis, called {\bf Locality Sensitive Discriminant Analysis} (LSDA).	Deng Cai; Xiaofei He; Kun Zhou; Jiawei Han; Hujun Bao;
2007	7	Conflict-Driven Answer Set Solving IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We introduce a new approach to computing answer sets of logic programs, based on concepts from constraint processing (CSP) and satisfiability checking (SAT).	Martin Gebser; Benjamin Kaufmann; André Neumann; Torsten Schaub;
2007	8	Document Summarization Using Conditional Random Fields IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present a Conditional Random Fields (CRF) based framework to keep the merits of the above two kinds of approaches while avoiding their disadvantages.	Dou Shen; Jian-Tao Sun; Hua Li; Qiang Yang; Zheng Chen;
2007	9	Conjunctive Query Answering For The Description Logic SHIQ IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we consider conjunctive queries over knowledge bases formulated in the popular DL SHIQ and allow transitive roles in both the query and the knowledge base.	Birte Glimm; Ian Horrocks; Carsten Lutz; Ulrike Sattler;
2007	10	Emergence Of Norms Through Social Learning IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a model that supports the emergence of social norms via learning from interaction experiences.	Sandip Sen; Stéphane Airiau;
2007	11	Identifying Expressions Of Opinion In Context IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present an approach for identifying opinion expressions that uses conditional random fields and we evaluate the approach at the expression-level using a standard sentiment corpus.	Eric Breck; Yejin Choi; Claire Cardie;
2007	12	Searching For Interacting Features IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Recognizing the presence of feature interaction, we propose to efficiently handle feature interaction to achieve efficient feature selection and present extensive experimental results of evaluation.	Zheng Zhao; Huan Liu;
2007	13	Formal Trust Model For Multiagent Systems IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: Hence an ability to combine evidence-based trust reports in a manner that discounts for imperfect trust in the reporting agents is crucial for multiagent systems.	Yonghong Wang; Munindar P. Singh;
2007	14	ItemRank: A Random-Walk Based Scoring Algorithm For Recommender Engines IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we present ItemRank, a random-walk based scoring algorithm, which can be used to rank products according to expected user preferences, in order to recommend top-rank items to potentially interested users.	Augusto Pucci; Marco Gori;
2007	15	Automatic Gait Optimization With Gaussian Process Regression IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We present a Bayesian approach based on Gaussian process regression that addresses all three drawbacks.	Daniel Lizotte; Tao Wang; Michael Bowling; Dale Schuurmans;
2005	1	Pushing The EL Envelope IF:8 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Franz Baader; Sebastian Brandt; and Carsten Lutz;
2005	2	A Hybrid Discriminative/Generative Approach For Modeling Human Activities IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Jonathan Lester; Tanzeem Choudhury; Nicky Kern; Gaetano Borriello; and Blake Hannaford;
2005	3	A Scalable Method For Multiagent Constraint Optimization IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Adrian Petcu and Boi Faltings;
2005	4	BLOG: Probabilistic Models With Unknown Objects IF:7 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	BRIAN MILCH et. al.
2005	5	A Tableaux Decision Procedure For SHOIQ IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Ian Horrocks and Ulrike Sattler;
2005	6	Location-Based Activity Recognition Using Relational Markov Networks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Lin Liao; Dieter Fox; and Henry Kautz;
2005	7	Topic And Role Discovery In Social Networks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Andrew McCallum; Andrés Corrada-Emmanuel; and Xuerui Wang;
2005	8	Lifted First-Order Probabilistic Inference IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Rodrigo de Salvo Braz; Eyal Amir; and Dan Roth;
2005	9	Feature Generation For Text Categorization Using World Knowledge IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Evgeniy Gabrilovich and Shaul Markovitch;
2005	10	Data Complexity Of Reasoning In Very Expressive Description Logics IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Ullrich Hustadt; Boris Motik; and Ulrike Sattler;
2005	11	A Uniform Integration Of Higher-Order Reasoning And External Evaluations In Answer-Set Programming IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Thomas Eiter; Giovambattista Ianni; Roman Schindlauer; and Hans Tompits;
2005	12	Automated Composition Of Web Services By Planning At The Knowledge Level IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	M. Pistore; A. Marconi; P. Bertoli; and P. Traverso;
2005	13	Beyond TFIDF Weighting For Text Categorization In The Vector Space Model IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Pascal Soucy and Guy W. Mineau;
2005	14	Networked Distributed POMDPs: A Synergy Of Distributed Constraint Optimization And POMDPs IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Ranjit Nair; Pradeep Varakantham; Milind Tambe; and Makoto Yokoo;
2005	15	Reasoning With Inconsistent Ontologies IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Zhisheng Huang; Frank van Harmelen; and Annette ten Teije;
2003	1	FastSLAM 2.0: An Improved Particle Filtering Algorithm For Simultaneous Localization And Mapping That Provably Converges IF:9 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Mike Montemerlo; Sebastian Thrun; Daphne Koller; and Ben Wegbreit;
2003	2	Point-based Value Iteration: An Anytime Algorithm For POMDPs IF:8 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Joelle Pineau; Geoff Gordon; and Sebastian Thrun;
2003	3	Extended Gloss Overlaps As A Measure Of Semantic Relatedness IF:8 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Satanjeev Banerjee and Ted Pedersen;
2003	4	Non-Standard Reasoning Services For The Debugging Of Description Logic Terminologies IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Stefan Schlobach and Ronald Cornet.;
2003	5	First-order Probabilistic Inference IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	David Poole.;
2003	6	AUC: A Statistically Consistent and More Discriminating Measure Than Accuracy IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Charles X. Ling; Jin Huang; and Harry Zhang.;
2003	7	Learning To Classify Texts Using Positive And Unlabeled Data IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Xiaoli Li and Bing Liu;
2003	8	Taming Decentralized POMDPs: Towards Efficient Policy Computation For Multiagent Settings IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	R. Nair; M. Tambe; M. Yokoo; D. Pynadath; and S. Marsella;
2003	9	DP-SLAM: Fast, Robust Simultaneous Localization And Mapping Without Predetermined Landmarks IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Austin Eliazar and Ronald Parr.;
2003	10	Challenges In Web Search Engines IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Monika R. Henzinger; Rajeev Motwani; and Craig Silverstein.;
2003	11	Backdoors To Typical Case Complexity IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Ryan Williams; Carla P. Gomes; and Bart Selman.;
2003	12	Constructing Diverse Classifier Ensembles Using Artificial Training Examples IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Prem Melville and Raymond J. Mooney;
2003	13	Model-based Diagnosis Of Hybrid Systems IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Sriram Narasimhan and Gautam Biswas.;
2003	14	Approximating Game-Theoretic Optimal Strategies For Full-scale Poker IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	D. BILLINGS et. al.
2003	15	Thin Junction Tree Filters For Simultaneous Localization And Mapping IF:5 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Mark A. Paskin.;