Most Influential IJCAI Papers (2021-02)

February 11, 2021March 9, 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 10 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 latest updates of the most influential papers from different 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: 2021-02)

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TABLE 1: Most Influential IJCAI Papers (2021-02)

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	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	5	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	6	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	7	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	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	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	10	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.
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	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	3	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	4	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	5	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	6	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	7	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	8	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	9	Graph Contextualized Self-Attention Network For Session-based Recommendation IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a graph contextualized self-attention model (GC-SAN), which utilizes both graph neural network and self-attention mechanism, for session-based recommendation.	CHENGFENG XU et. al.
2019	10	Meta-Learning For Low-resource Natural Language Generation In Task-oriented Dialogue Systems IF:3 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we study NLG in a low-resource setting to generate sentences in new scenarios with handful training examples.	Fei Mi; Minlie Huang; Jiyong Zhang; Boi Faltings;
2018	1	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	2	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	3	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	4	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	5	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	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	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	8	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	9	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	10	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	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	3	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	4	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	5	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	6	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	7	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	8	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	9	What To Do Next: Modeling User Behaviors By Time-LSTM IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we propose a new LSTM variant, i.e. Time-LSTM, to model users’ sequential actions.	YU ZHU et. al.
2017	10	Tactics Of Adversarial Attack On Deep Reinforcement Learning Agents IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: We propose a novel method to determine when an adversarial example should be crafted and applied.	YEN-CHEN LIN et. al.
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	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	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	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	8	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	9	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	10	DeepTransport: Prediction And Simulation Of Human Mobility And Transportation Mode At A Citywide Level IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this study, we collect big and heterogeneous data (e.g., GPS records and transportation network data), and we build an intelligent system, namely DeepTransport, for simulating and predicting human mobility and transportation mode at a citywide level.	Xuan Song; Hiroshi Kanasugi; Ryosuke Shibasaki;
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	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	7	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	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	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;
2013	1	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	2	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	3	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	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	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	6	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	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	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	9	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	10	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;
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	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	4	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	5	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	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	A Graph-Based Algorithm For Inducing Lexical Taxonomies From Scratch IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper we present a graph-based approach aimed at learning a lexical taxonomy automatically starting from a domain corpus and the Web.	Roberto Navigli; Paola Velardi; Stefano Faralli;
2011	10	Multi-Label Classification Using Conditional Dependency Networks IF:4 Related Papers Related Patents Related Grants Related Orgs Related Experts Details Highlight: In this paper, we tackle the challenges of multi-label classification by developing a general conditional dependency network model.	Yuhong Guo; Suicheng Gu;
2009	1	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	2	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	3	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	4	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	5	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	6	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	7	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	8	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	9	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	10	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;
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	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	4	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	5	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	6	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	7	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	8	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	9	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	10	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;
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	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	6	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	7	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	8	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	9	Identifiability Of Path-Specific Effects IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	Chen Avin; Ilya Shpitser; and Judea Pearl;
2005	10	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;
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	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	5	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	6	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	7	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	8	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	9	First-order Probabilistic Inference IF:6 Related Papers Related Patents Related Grants Related Orgs Related Experts Details	David Poole.;
2003	10	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.;