IJCAI 2018

870 papers

Discrete Interventions in Hawkes Processes with Applications in Invasive Species Management

Amrita Gupta, Mehrdad Farajtabar, Bistra Dilkina, Hongyuan Zha

Recommendation with Multi-Source Heterogeneous Information

Li Gao, Hong Yang, Jia Wu, Chuan Zhou, Weixue Lu

Interpretable Drug Target Prediction Using Deep Neural Representation

Kyle Yingkai Gao, Achille Fokoue, Heng Luo, Arun Iyengar, Sanjoy Dey

Deep Attributed Network Embedding

Hongchang Gao, Heng Huang

Automatic Opioid User Detection from Twitter: Transductive Ensemble Built on Different Meta-graph Based Similarities over Heterogeneous Information Network

Yujie Fan, Yiming Zhang, Yanfang Ye, Xin Li

Recurrent Collaborative Filtering for Unifying General and Sequential Recommender

Disheng Dong, Xiaolin Zheng, Ruixun Zhang, Yan Wang

Improving Implicit Recommender Systems with View Data

Jingtao Ding, Guanghui Yu, Xiangnan He, Yuhan Quan, Yong Li

Learning to Recognize Transient Sound Events using Attentional Supervision

Szu-Yu Chou, Jyh-Shing Jang, Yi-Hsuan Yang

DELF: A Dual-Embedding based Deep Latent Factor Model for Recommendation

Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang

Predicting Complex Activities from Ongoing Multivariate Time Series

Weihao Cheng, Sarah Erfani, Rui Zhang, Ramamohanarao Kotagiri

NeuCast: Seasonal Neural Forecast of Power Grid Time Series

Pudi Chen, Shenghua Liu, Chuan Shi, Bryan Hooi, Bai Wang

Beyond the Click-Through Rate: Web Link Selection with Multi-level Feedback

Kun Chen, Kechao Cai, Longbo Huang, John C.S. Lui

Content-Aware Hierarchical Point-of-Interest Embedding Model for Successive POI Recommendation

Buru Chang, Yonggyu Park, Donghyeon Park, Seongsoon Kim, Jaewoo Kang

A Fast and Accurate Method for Estimating People Flow from Spatiotemporal Population Data

Yasunori Akagi, Takuya Nishimura, Takeshi Kurashima, Hiroyuki Toda

Sampling for Approximate Bipartite Network Projection

Nesreen Ahmed, Nick Duffield, Liangzhen Xia

Robust Multi-view Learning via Half-quadratic Minimization

Yonghua Zhu, Xiaofeng Zhu, Wei Zheng

Localized Incomplete Multiple Kernel k-means

Xinzhong Zhu, Xinwang Liu, Miaomiao Li, En Zhu, Li Liu

Improving Deep Neural Network Sparsity through Decorrelation Regularization

Xiaotian Zhu, Wengang Zhou, Houqiang Li

Robust Graph Dimensionality Reduction

Xiaofeng Zhu, Cong Lei, Hao Yu, Yonggang Li, Jiangzhang Gan

Fast Model Identification via Physics Engines for Data-Efficient Policy Search

Shaojun Zhu, Andrew Kimmel, Kostas E. Bekris, Abdeslam Boularias

Pengfei Zhu, Ren Qi, Qinghua Hu, Qilong Wang, Changqing Zhang

Towards Generalized and Efficient Metric Learning on Riemannian Manifold

Pengfei Zhu, Hao Cheng, Qinghua Hu, Qilong Wang, Changqing Zhang

Cost-aware Cascading Bandits

Ruida Zhou, Chao Gan, Jing Yang, Cong Shen

On the Convergence Properties of a K-step Averaging Stochastic Gradient Descent Algorithm for Nonconvex Optimization

Fan Zhou, Guojing Cong

Trajectory-User Linking via Variational AutoEncoder

Fan Zhou, Qiang Gao, Goce Trajcevski, Kunpeng Zhang, Ting Zhong

Where to Prune: Using LSTM to Guide End-to-end Pruning

Jing Zhong, guiguang ding, Yuchen Guo, Jungong Han, Bin Wang

Self-Adaptive Double Bootstrapped DDPG

Zhuobin Zheng, Chun Yuan, Zhihui Lin, Yangyang Cheng, Hanghao Wu

Robust Feature Selection on Incomplete Data

Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang

Attentional Image Retweet Modeling via Multi-Faceted Ranking Network Learning

Zhou Zhao, Lingtao Meng, Jun Xiao, Min Yang, Fei Wu

Grouping Attribute Recognition for Pedestrian with Joint Recurrent Learning

Xin Zhao, Liufang Sang, guiguang ding, Yuchen Guo, Xiaoming Jin

Deep Convolutional Neural Networks with Merge-and-Run Mappings

Liming Zhao, Mingjie Li, Depu Meng, Xi Li, Zhaoxiang Zhang

Dynamic Hypergraph Structure Learning

Zizhao Zhang, Haojie Lin, Yue Gao

ANRL: Attributed Network Representation Learning via Deep Neural Networks

Zhen Zhang, Hongxia Yang, Jiajun Bu, Sheng Zhou, Pinggang Yu

Distributed Self-Paced Learning in Alternating Direction Method of Multipliers

Xuchao Zhang, Liang Zhao, Zhiqian Chen, Chang-Tien Lu

Self-Supervised Deep Low-Rank Assignment Model for Prototype Selection

Xingxing Zhang, Zhenfeng Zhu, Yao Zhao, Deqiang Kong

Multi-Task Clustering with Model Relation Learning

Xiaotong Zhang, Xianchao Zhang, Han Liu, Jiebo Luo

Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning

Xiao Zhang, Wenzhong Li, Vu Nguyen, Fuzhen Zhuang, Hui Xiong

Online Kernel Selection via Incremental Sketched Kernel Alignment

Xiao Zhang, Shizhong Liao

Multi-modality Sensor Data Classification with Selective Attention

Xiang Zhang, Lina Yao, Chaoran Huang, Sen Wang, Mingkui Tan

Semi-Supervised Optimal Margin Distribution Machines

Teng Zhang, Zhi-Hua Zhou

Achieving Non-Discrimination in Prediction

Lu Zhang, Yongkai Wu, Xintao Wu

Dynamically Hierarchy Revolution: DirNet for Compressing Recurrent Neural Network on Mobile Devices

Jie Zhang, Xiaolong Wang, Dawei Li, Yalin Wang

Scalable Multiplex Network Embedding

Hongming Zhang, Liwei Qiu, Lingling Yi, Yangqiu Song

Generative Warfare Nets: Ensemble via Adversaries and Collaborators

Honglun Zhang, Liqiang Xiao, Wenqing Chen, Yongkun Wang, Yaohui Jin

Learning to Design Games: Strategic Environments in Reinforcement Learning

Haifeng Zhang, Jun Wang, Zhiming Zhou, Weinan Zhang, Yin Wen

Learning Environmental Calibration Actions for Policy Self-Evolution

Chao Zhang, Yang Yu, Zhi-Hua Zhou

FISH-MML: Fisher-HSIC Multi-View Metric Learning

Changqing Zhang, Yeqinq Liu, Yue Liu, Qinghua Hu, Xinwang Liu

Mixture of GANs for Clustering

Yang Yu, Wen-Ji Zhou

A Generic Approach for Accelerating Stochastic Zeroth-Order Convex Optimization

Xiaotian Yu, Irwin King, Michael R. Lyu, Tianbao Yang

Request-and-Reverify: Hierarchical Hypothesis Testing for Concept Drift Detection with Expensive Labels

Shujian Yu, Xiaoyang Wang, José C. Príncipe

Hashing over Predicted Future Frames for Informed Exploration of Deep Reinforcement Learning

Haiyan Yin, Jianda Chen, Sinno Jialin Pan

Stochastic Fractional Hamiltonian Monte Carlo

Nanyang Ye, Zhanxing Zhu

Distance Metric Facilitated Transportation between Heterogeneous Domains

Han-Jia Ye, Xiang-Rong Sheng, De-Chuan Zhan, Peng He

High-dimensional Similarity Learning via Dual-sparse Random Projection

Dezhong Yao, Peilin Zhao, Tuan-Anh Nguyen Pham, Gao Cong

Semi-Supervised Multi-Modal Learning with Incomplete Modalities

Yang Yang, De-Chuan Zhan, Xiang-Rong Sheng, Yuan Jiang

Bandit Online Learning on Graphs via Adaptive Optimization

Peng Yang, Peilin Zhao, Xin Gao

A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning

Long Yang, Minhao Shi, Qian Zheng, Wenjia Meng, Gang Pan

Spatio-Temporal Check-in Time Prediction with Recurrent Neural Network based Survival Analysis

Guolei Yang, Ying Cai, Chandan K Reddy

Semi-Supervised Optimal Transport for Heterogeneous Domain Adaptation

Yuguang Yan, Wen Li, Hanrui Wu, Huaqing Min, Mingkui Tan

Cost-Effective Active Learning for Hierarchical Multi-Label Classification

Yi-Fan Yan, Sheng-jun Huang

A Unified Analysis of Stochastic Momentum Methods for Deep Learning

Yan Yan, Tianbao Yang, Zhe Li, Qihang Lin, Yi Yang

Improving Maximum Likelihood Estimation of Temporal Point Process via Discriminative and Adversarial Learning

Junchi Yan, Xin Liu, Liangliang Shi, Changsheng Li, Hongyuan Zha

PredCNN: Predictive Learning with Cascade Convolutions

Ziru Xu, Yunbo Wang, Mingsheng Long, Jianmin Wang

Convergence Analysis of Gradient Descent for Eigenvector Computation

Zhiqiang Xu, Xin Cao, Xin Gao

Label Enhancement for Label Distribution Learning

Ning Xu, An Tao, Xin Geng

Multi-Level Metric Learning via Smoothed Wasserstein Distance

Jie Xu, Lei Luo, Cheng Deng, Heng Huang

MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling

Jianpeng Xu, Xi Liu, Tyler Wilson, Pang-Ning Tan, Pouyan Hatami

Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes

Hongteng Xu, Dixin Luo, Lawrence Carin

Deep Multi-View Concept Learning

Cai Xu, Ziyu Guan, Wei Zhao, Yunfei Niu, Quan Wang

De-biasing Covariance-Regularized Discriminant Analysis

Haoyi Xiong, Wei Cheng, Yanjie Fu, Wenqing Hu, Jiang Bian

Multi-Label Co-Training

Yuying Xing, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang

Cutting the Software Building Efforts in Continuous Integration by Semi-Supervised Online AUC Optimization

Zheng Xie, Ming Li

Towards Enabling Binary Decomposition for Partial Label Learning

Xuan Wu, Min-ling Zhang

Efficient Attributed Network Embedding via Recursive Randomized Hashing

Wei Wu, Bin Li, Ling Chen, Chengqi Zhang

Unsupervised Deep Hashing via Binary Latent Factor Models for Large-scale Cross-modal Retrieval

Gengshen Wu, Zijia Lin, Jungong Han, Li Liu, guiguang ding

Does Tail Label Help for Large-Scale Multi-Label Learning

Tong Wei, Yu-feng Li

Positive and Unlabeled Learning for Detecting Software Functional Clones with Adversarial Training

Hui-Hui Wei, Ming Li

Fast Factorization-free Kernel Learning for Unlabeled Chunk Data Streams

Yi Wang, Nan Xue, Xin Fan, Jiebo Luo, Risheng Liu

New Balanced Active Learning Model and Optimization Algorithm

Xiaoqian Wang, Yijun Huang, Ji Liu, Heng Huang

Mixed Link Networks

Wenhai Wang, Xiang Li, Tong Lu, Jian Yang

Feature Hashing for Network Representation Learning

Qixiang Wang, Shanfeng Wang, Maoguo Gong, Yue Wu

Iterative Metric Learning for Imbalance Data Classification

Nan Wang, Xibin Zhao, Yu Jiang, Yue Gao

Adaptive Graph Guided Embedding for Multi-label Annotation

Lichen Wang, Zhengming Ding, Yun Fu

Convolutional Memory Blocks for Depth Data Representation Learning

Keze Wang, Liang Lin, Chuangjie Ren, Wei Zhang, Wenxiu Sun

Binary Coding based Label Distribution Learning

Ke Wang, Xin Geng

Ranking Preserving Nonnegative Matrix Factorization

Jing Wang, Feng Tian, Weiwei Liu, Xiao Wang, Wenjie Zhang

Progressive Blockwise Knowledge Distillation for Neural Network Acceleration

Hui Wang, Hanbin Zhao, Xi Li, Xu Tan

Minimizing Adaptive Regret with One Gradient per Iteration

Guanghui Wang, Dakuan Zhao, Lijun Zhang

Cascaded Low Rank and Sparse Representation on Grassmann Manifolds

Boyue Wang, Yongli Hu, Junbin Gao, Yanfeng Sun, Baocai Yin

Efficient Adaptive Online Learning via Frequent Directions

Yuanyu Wan, Nan Wei, Lijun Zhang

Deterministic Binary Filters for Convolutional Neural Networks

Vincent W.-S. Tseng, Sourav Bhattacharya, Javier Fernández Marqués, Milad Alizadeh, Catherine Tong

Differentiable Submodular Maximization

Sebastian Tschiatschek, Aytunc Sahin, Andreas Krause

Deep into Hypersphere: Robust and Unsupervised Anomaly Discovery in Dynamic Networks

Xian Teng, Muheng Yan, Ali Mert Ertugrul, Yu-Ru Lin

Algorithms or Actions? A Study in Large-Scale Reinforcement Learning

Anderson Rocha Tavares, Sivasubramanian Anbalagan, Leandro Soriano Marcolino, Luiz Chaimowicz

Exploration by Distributional Reinforcement Learning

Yunhao Tang, Shipra Agrawal

Incomplete Multi-View Weak-Label Learning

Qiaoyu Tan, Guoxian Yu, Carlotta Domeniconi, Jun Wang, Zili Zhang

Student-t Variational Autoencoder for Robust Density Estimation

Hiroshi Takahashi, Tomoharu Iwata, Yuki Yamanaka, Masanori Yamada, Satoshi Yagi

Positive and Unlabeled Learning via Loss Decomposition and Centroid Estimation

Hong Shi, Shaojun Pan, Jian Yang, Chen Gong

Refine or Represent: Residual Networks with Explicit Channel-wise Configuration

Yanyan Shen, Jinyang Gao

Deep Discrete Prototype Multilabel Learning

Xiaobo Shen, Weiwei Liu, Yong Luo, Yew-Soon Ong, Ivor W. Tsang