IJCAI 2017

781 papers

Efficiency Through Procrastination: Approximately Optimal Algorithm Configuration with Runtime Guarantees

Robert Kleinberg, Kevin Leyton-brown, Brendan Lucier

DeepStory: Video Story QA by Deep Embedded Memory Networks

Kyung-Min Kim, Min-Oh Heo, Seong-Ho Choi, Byoung-tak Zhang

Learning deep structured network for weakly supervised change detection

Salman Khan, Xuming He, Fatih Porikli, Mohammed Bennamoun, Ferdous Sohel

Bernoulli Rank-1 Bandits for Click Feedback

Sumeet Katariya, Branislav Kveton, Csaba Szepesvári, Claire Vernade, Zheng Wen

Modelling the Working Week for Multi-Step Forecasting using Gaussian Process Regression

Pasan Karunaratne, Masud Moshtaghi, Shanika Karunasekera, Aaron Harwood, Trevor Cohn

A Functional Dynamic Boltzmann Machine

Hiroshi Kajino

Confusion Graph: Detecting Confusion Communities in Large Scale Image Classification

Ruochun Jin, Yong Dou, Yueqing Wang, Xin Niu

Improving Classification Accuracy of Feedforward Neural Networks for Spiking Neuromorphic Chips

Antonio Jimeno Yepes, Jianbin Tang, Benjamin Scott Mashford

Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering

Zhuxi Jiang, Yin Zheng, Huachun Tan, Bangsheng Tang, Hanning Zhou

Theoretic Analysis and Extremely Easy Algorithms for Domain Adaptive Feature Learning

Wenhao Jiang, Cheng Deng, Wei Liu, Feiping Nie, Fu-lai Chung

Exploration of Tree-based Hierarchical Softmax for Recurrent Language Models

Nan Jiang, Wenge Rong, Min Gao, Yikang Shen, Zhang Xiong

Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks

He Jiang, Yangqiu Song, Chenguang Wang, Ming Zhang, Yizhou Sun

Embedding-based Representation of Categorical Data by Hierarchical Value Coupling Learning

Songlei Jian, Longbing Cao, Guansong Pang, Kai Lu, Hang Gao

Privacy Issues Regarding the Application of DNNs to Activity-Recognition using Wearables and Its Countermeasures by Use of Adversarial Training

Yusuke Iwasawa, Kotaro Nakayama, Ikuko Yairi, Yutaka Matsuo

Adaptive Learning Rate via Covariance Matrix Based Preconditioning for Deep Neural Networks

Yasutoshi Ida, Yasuhiro Fujiwara, Sotetsu Iwamura

Ordinal Zero-Shot Learning

Zengwei Huo, Xin Geng

Enhancing the Unified Features to Locate Buggy Files by Exploiting the Sequential Nature of Source Code

Xuan Huo, Ming Li

Incremental Matrix Factorization: A Linear Feature Transformation Perspective

Xunpeng Huang, Le Wu, Enhong Chen, Hengshu Zhu, Qi Liu

Cross-modal Common Representation Learning by Hybrid Transfer Network

Xin Huang, Yuxin Peng, Mingkuan Yuan

Multi-instance multi-label active learning

Sheng-jun Huang, Nengneng Gao, Songcan Chen

Cost-Effective Active Learning from Diverse Labelers

Sheng-jun Huang, Jia-Lve Chen, Xin Mu, Zhi-Hua Zhou

Mention Recommendation for Twitter with End-to-end Memory Network

Haoran Huang, Qi Zhang, Xuanjing Huang

Semi-supervised Max-margin Topic Model with Manifold Posterior Regularization

Wenbo Hu, Jun Zhu, Hang Su, Jingwei Zhuo, Bo Zhang

Diversifying Personalized Recommendation with User-session Context

Liang Hu, Longbing Cao, Shoujin Wang, Guandong Xu, Jian Cao

Fast Recursive Low-rank Tensor Learning for Regression

Ming Hou, Brahim Chaib-draa

Storage Fit Learning with Unlabeled Data

Bo-Jian Hou, Lijun Zhang, Zhi-Hua Zhou

Category-aware Next Point-of-Interest Recommendation via Listwise Bayesian Personalized Ranking

Jing He, Xin Li, Lejian Liao

Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel

Jia He, Changying Du, Changde Du, Fuzhen Zhuang, Qing He

Online Multitask Relative Similarity Learning

Shuji Hao, Peilin Zhao, Yong Liu, Steven C. H. Hoi, Chunyan Miao

Self-paced Mixture of Regressions

Longfei Han, Dingwen Zhang, Dong Huang, Xiaojun Chang, Jun Ren

Orthogonal and Nonnegative Graph Reconstruction for Large Scale Clustering

Junwei Han, Kai Xiong, Feiping Nie

Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach

Takuo Hamaguchi, Hidekazu Oiwa, Masashi Shimbo, Yuji Matsumoto

Instability Prediction in Power Systems using Recurrent Neural Networks

Ankita Gupta, Gurunath Gurrala, Pidaparthy S Sastry

Improved Strong Worst-case Upper Bounds for MDP Planning

Anchit Gupta, Shivaram Kalyanakrishnan

Understanding Users' Budgets for Recommendation with Hierarchical Poisson Factorization

Yunhui Guo, Congfu Xu, Hanzhang Song, Xin Wang

Synthesizing Samples for Zero-shot Learning

Yuchen Guo, guiguang ding, Jungong Han, Yue Gao

SitNet: Discrete Similarity Transfer Network for Zero-shot Hashing

Yuchen Guo, guiguang ding, Jungong Han, Yue Gao

Robust Asymmetric Bayesian Adaptive Matrix Factorization

Xin Guo, Boyuan Pan, Deng Cai, Xiaofei He

Improved Deep Embedded Clustering with Local Structure Preservation

Xifeng Guo, Long Gao, Xinwang Liu, Jianping Yin

ROUTE: Robust Outlier Estimation for Low Rank Matrix Recovery

Xiaojie Guo, Zhouchen Lin

Exclusivity Regularized Machine: A New Ensemble SVM Classifier

Xiaojie Guo, Xiaobo Wang, Haibin Ling

A Density-based Nonparametric Model for Online Event Discovery from the Social Media Data

Jinjin Guo, Zhiguo Gong

DeepFM: A Factorization-Machine based Neural Network for CTR Prediction

Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, Xiuqiang He

Extracting Visual Knowledge from the Web with Multimodal Learning

Dihong Gong, Daisy Zhe Wang

Sample Efficient Policy Search for Optimal Stopping Domains

Karan Goel, Christoph Dann, Emma Brunskill

Towards Understanding the Invertibility of Convolutional Neural Networks

Anna Gilbert, Yi Zhang, Kibok Lee, Yuting Zhang, Honglak Lee

Neurogenesis-Inspired Dictionary Learning: Online Model Adaption in a Changing World

Sahil Garg, Irina Rish, Guillermo Cecchi, Aurélie Lozano

Identifying Human Mobility via Trajectory Embeddings

Qiang Gao, Fan Zhou, Kunpeng Zhang, Goce Trajcevski, Xucheng Luo

SVD-Based Screening for the Graphical Lasso

Yasuhiro Fujiwara, Naoki Marumo, Mathieu Blondel, Koh Takeuchi, Hideaki Kim

On the Complexity of Learning from Label Proportions

Benjamin Fish, Lev Reyzin

Dynamic Multi-Task Learning with Convolutional Neural Network

Yuchun Fang, Zhengyan Ma, Zhaoxiang Zhang, Xu-yao Zhang, Xiang Bai

Object Detection Meets Knowledge Graphs

Yuan Fang, Kingsley Kuan, Jie Lin, Cheston Tan, Vijay Chandrasekhar

Improved Bounded Matrix Completion for Large-Scale Recommender Systems

Huang Fang, Zhang Zhen, Yiqun Shao, Cho-jui Hsieh

Top-k Supervise Feature Selection via ADMM for Integer Programming

Mingyu Fan, Xiaojun Chang, Xiaoqin Zhang, Di Wang, Liang Du

Learning to Learn Programs from Examples: Going Beyond Program Structure

Kevin Ellis, Sumit Gulwani

Clustering-Based Relational Unsupervised Representation Learning with an Explicit Distributed Representation

Sebastijan Dumancic, Hendrik Blockeel

Semi-Supervised Learning for Surface EMG-based Gesture Recognition

Yu Du, Yongkang Wong, Wenguang Jin, Wentao Wei, YU HU

Collaborative Rating Allocation

Yali Du, Chang Xu, Dacheng Tao

Privileged Matrix Factorization for Collaborative Filtering

Yali Du, Chang Xu, Dacheng Tao

Autoencoder Regularized Network For Driving Style Representation Learning

Weishan Dong, Ting Yuan, Kai Yang, Changsheng Li, Shilei Zhang

Logic Tensor Networks for Semantic Image Interpretation

Ivan Donadello, Luciano Serafini, Artur d'Avila Garcez

Disguise Adversarial Networks for Click-through Rate Prediction

Yue Deng, Yilin Shen, Hongxia Jin

Real-Time Navigation in Classical Platform Games via Skill Reuse

Michael Dann, Fabio Zambetta, John Thangarajah

Analogy-preserving functions: A way to extend Boolean samples

Miguel Couceiro, Nicolas Hug, Henri Prade, Gilles Richard

Further Results on Predicting Cognitive Abilities for Adaptive Visualizations

Cristina Conati, Sébastien Lallé, Md. Abed Rahman, Dereck Toker

Stacked Similarity-Aware Autoencoders

Wenqing Chu, Deng Cai

Optimal Feature Selection for Decision Robustness in Bayesian Networks

YooJung Choi, Adnan Darwiche, Guy Van den Broeck

End-to-End Prediction of Buffer Overruns from Raw Source Code via Neural Memory Networks

Min-je Choi, Sehun Jeong, Hakjoo Oh, Jaegul Choo

Projection Free Rank-Drop Steps

Edward Cheung, Yuying Li

Training Group Orthogonal Neural Networks with Privileged Information

Yunpeng Chen, Xiaojie Jin, Jiashi Feng, Shuicheng Yan

Semi-supervised Feature Selection via Rescaled Linear Regression

Xiaojun Chen, Guowen Yuan, Feiping Nie, Joshua Zhexue Huang

Scalable Normalized Cut with Improved Spectral Rotation

Xiaojun Chen, Feiping Nie, Joshua Zhexue Huang, Min Yang

Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

Muhao Chen, Yingtao Tian, Mohan Yang, Carlo Zaniolo

Importance-Aware Semantic Segmentation for Autonomous Driving System

Bi-ke Chen, Chen Gong, Jian Yang

Data-driven Random Fourier Features using Stein Effect

Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos

Encoding and Recall of Spatio-Temporal Episodic Memory in Real Time

Poo-Hee Chang, Ah-Hwee Tan

Multiple-Weight Recurrent Neural Networks

Zhu Cao, Linlin Wang, Gerard de Melo

SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation

Chenwei Cai, Ruining He, Julian McAuley

Context Attentive Bandits: Contextual Bandit with Restricted Context

Djallel Bouneffouf, Irina Rish, Guillermo Cecchi, Raphaël Féraud

Human-Centric Justification of Machine Learning Predictions

Or Biran, Kathleen McKeown

Using Graphs of Classifiers to Impose Declarative Constraints on Semi-supervised Learning

Lidong Bing, William W. Cohen, Bhuwan Dhingra

Unsupervised Learning of Deep Feature Representation for Clustering Egocentric Actions

Bharat Lal Bhatnagar, Suriya Singh, Chetan Arora, C.V. Jawahar

AccGenSVM: Selectively Transferring from Previous Hypotheses

Diana Benavides-Prado, Yun Sing Koh, Patricia Riddle

Handling Noise in Boolean Matrix Factorization

Radim Belohlavek, Martin Trnecka

Mining Convex Polygon Patterns with Formal Concept Analysis

Aimene Belfodil, Sergei O. Kuznetsov, Céline Robardet, Mehdi Kaytoue

Efficient Reinforcement Learning with Hierarchies of Machines by Leveraging Internal Transitions

Aijun Bai, Stuart Russell

Bayesian Aggregation of Categorical Distributions with Applications in Crowdsourcing

Alexandry Augustin, Matteo Venanzi, Alex Rogers, Nicholas R. Jennings

Universal Reinforcement Learning Algorithms: Survey and Experiments

John Aslanides, Jan Leike, Marcus Hutter

Grounding of Human Environments and Activities for Autonomous Robots

Muhannad Alomari, Paul Duckworth, Nils Bore, Majd Hawasly, David C. Hogg

RHash: Robust Hashing via L_infinity-norm Distortion

Amirali Aghazadeh, Andrew Lan, Anshumali Shrivastava, Richard Baraniuk

Contextual Covariance Matrix Adaptation Evolutionary Strategies

Abbas Abdolmaleki, Bob Price, Nuno Lau, Luís Paulo Reis, Gerhard Neumann

A Unifying Framework for Probabilistic Belief Revision

Zhiqiang Zhuang, James Delgrande, Abhaya Nayak, Abdul Sattar

Symbolic LTLf Synthesis

Shufang Zhu, Lucas M. Tabajara, Jianwen Li, Geguang Pu, Moshe Y. Vardi

Role Forgetting for ALCOQH(universal role)-Ontologies Using an Ackermann-Based Approach

Yizheng Zhao, Renate A. Schmidt

Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination

Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf

Transfer Learning in Multi-Armed Bandits: A Causal Approach

Junzhe Zhang, Elias Bareinboim

Proposing a Highly Accurate Hybrid Component-Based Factorised Preference Model in Recommender Systems

Farhad Zafari, Rasoul Rahmani, Irene Moser

Aggregating Crowd Wisdoms with Label-aware Autoencoders

Li'ang Yin, Jianhua Han, Weinan Zhang, Yong Yu

Knowledge Graph Representation with Jointly Structural and Textual Encoding

Jiacheng Xu, Xipeng Qiu, Kan Chen, Xuanjing Huang

Efficient Inference and Computation of Optimal Alternatives for Preference Languages Based On Lexicographic Models

Nic Wilson, Anne-Marie George