Accept papers: link

anomaly detection (anomaly, outlier, out-of-distribution, one-class, Malware detection, Fraud Detection, Fake News Detection)

• Masked Contrastive Learning for Anomaly Detection

  Hyunsoo Cho (Seoul National University)
  Jinseok Seol (Seoul National University)
  Sang-goo Lee (Seoul National University)

• Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video

  Jie Wu (Sun Yat-sen University ByteDance Inc.)
  Wei Zhang (Baidu Inc.)
  Guanbin Li (Sun Yat-sen University)
  Wenhao Wu (Baidu Inc.)
  Xiao Tan (Baidu Inc.)
  Yingying Li (Baidu Inc.)
  Errui Ding (Baidu Inc.)
  Liang Lin (Sun Yat-sen University)

• RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection

  Boyang Liu (Michigan State University)
  Ding Wang (Michigan State University)
  Kaixiang Lin (Michigan State University)
  Pang-Ning Tan (Michigan State University)
  Jiayu Zhou (Michigan State University)

• Understanding the Effect of Bias in Deep Anomaly Detection

  Ziyu Ye (University of Chicago)
  Yuxin Chen (University of Chicago)
  Haitao Zheng (University of Chicago)

• Likelihood-free Out-of-Distribution Detection with Invertible Generative Models

  Amirhossein Ahmadian (Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University)
  Fredrik Lindsten (Division of Statistics and Machine Learning, Department of Computer and Information Science, Linköping University)

• MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

  Chen Liu (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Bo Li (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Jun Zhao (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Ming Su (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Xu-Dong Liu (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)

• Online Credit Payment Fraud Detection via Structure-Aware Hierarchical Recurrent Neural Network

  Wangli Lin (Alibaba Group, Hangzhou, China)
  Li Sun (Alibaba Group, Hangzhou, China)
  Qiwei Zhong (Alibaba Group, Hangzhou, China)
  Can Liu (Alibaba Group, Hangzhou, China)
  Jinghua Feng (Alibaba Group, Hangzhou, China)
  Xiang Ao (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)
  Hao Yang (Alibaba Group, Hangzhou, China)

Time series

• Time-Series Representation Learning via Temporal and Contextual Contrasting

  Emadeldeen Eldele (School of Computer Science and Engineering, Nanyang Technological University, Singapore)
  Mohamed Ragab (School of Computer Science and Engineering, Nanyang Technological University, Singapore)
  Zhenghua Chen (Institute for Infocomm Research, ASTAR, Singapore)
  Min Wu (Institute for Infocomm Research, ASTAR, Singapore)
  Chee Keong Kwoh (School of Computer Science and Engineering, Nanyang Technological University, Singapore)
  Xiaoli Li (Institute for Infocomm Research, A*STAR, Singapore)
  Cuntai Guan (School of Computer Science and Engineering, Nanyang Technological University, Singapore)

• TE-ESN: Time Encoding Echo State Network for Prediction Based on Irregularly Sampled Time Series Data

  Chenxi Sun (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)
  Shenda Hong (National Institute of Health Data Science, Peking University, Beijing, China. Institute of Medical Technology, Health Science Center of Peking University, Beijing, China.)
  Moxian Song (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)
  Yen-Hsiu Chou (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)
  Yongyue Sun (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)
  Derun Cai (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)
  Hongyan Li (Key Laboratory of Machine Perception (Ministry of Education), Peking University, Beijing, China. School of Electronics Engineering and Computer Science, Peking University, Beijing, China.)

• Time-Aware Multi-Scale RNNs for Time Series Modeling

  Zipeng Chen (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China)
  Qianli Ma (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China Key Laboratory of Big Data and Intelligent Robot (South China University of Technology), Ministry of Education)
  Zhenxi Lin (School of Computer Science and Engineering, South China University of Technology, Guangzhou, China)

• Adversarial Spectral Kernel Matching for Unsupervised Time Series Domain Adaptation

  Qiao Liu (School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China MOE Key Laboratory of Computer Network and Information Integration (Southeast University))
  Hui Xue (School of Computer Science and Engineering, Southeast University, Nanjing, 210096, China MOE Key Laboratory of Computer Network and Information Integration (Southeast University))

• Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting

  Qingyi Pan (High Performance Computing Group, Dept. of Comp. Sci. and Tech., BNRist Center, Institute for AI, Tsinghua-Bosch Joint ML Center, THBI Lab, Tsinghua University, Beijing, 100084 China)
  Wenbo Hu (RealAI)
  Ning Chen (High Performance Computing Group, Dept. of Comp. Sci. and Tech., BNRist Center, Institute for AI, Tsinghua-Bosch Joint ML Center, THBI Lab, Tsinghua University, Beijing, 100084 China)

heterogeneous (multi-source)

• Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection

  Yiyue Qian (Department of Computer and Data Sciences, Case Western Reserve University, USA)
  Yiming Zhang (Department of Computer and Data Sciences, Case Western Reserve University, USA)
  Yanfang Ye (Department of Computer and Data Sciences, Case Western Reserve University, USA)
  Chuxu Zhang (Department of Computer Science, Brandeis University, USA)

• Temporal Heterogeneous Information Network Embedding

  Hong Huang (National Engineering Research Center for Big Data Technology and System Service Computing Technology and Systems Laboratory Huazhong University of Science and Technology, China)
  Ruize Shi (National Engineering Research Center for Big Data Technology and System Service Computing Technology and Systems Laboratory Huazhong University of Science and Technology, China)
  Wei Zhou (Huazhong University of Science and Technology, China)
  Xiao Wang (Beijing University of Posts and Telecommunications, China)
  Hai Jin (National Engineering Research Center for Big Data Technology and System Service Computing Technology and Systems Laboratory Huazhong University of Science and Technology, China)
  Xiaoming Fu (University of Goettingen, Germany)

Graph Representation Learning

• MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

  Chen Liu (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Bo Li (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Jun Zhao (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Ming Su (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)
  Xu-Dong Liu (School of Computer Science and Engineering, Beihang University, Beijing, China Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, China)

• Heterogeneous Graph Information Bottleneck

  Liang Yang (Hebei University of Technology, Tianjin, China Institute of Information Engineering, CAS, Beijing, China)
  Fan Wu (Hebei University of Technology, Tianjin, China)
  Zichen Zheng (Hebei University of Technology, Tianjin, China)
  Bingxin Niu (Hebei University of Technology, Tianjin, China)
  Junhua Gu (Hebei University of Technology, Tianjin, China)
  Chuan Wang (Institute of Information Engineering, CAS, Beijing, China)
  Xiaochun Cao (Institute of Information Engineering, CAS, Beijing, China)
  Yuanfang Guo (Beihang University, Beijing, China)

• Learning Attributed Graph Representation with Communicative Message Passing Transformer

  Jianwen Chen (School of Computer Science and Engineering, Sun Yat-sen University)
  Shuangjia Zheng (School of Computer Science and Engineering, Sun Yat-sen University Galixir Technologies Ltd, Beijing)
  Ying Song (School of System Science and Engineering, Sun Yat-sen University)
  Jiahua Rao (School of Computer Science and Engineering, Sun Yat-sen University Galixir Technologies Ltd, Beijing)
  Yuedong Yang (School of Computer Science and Engineering, Sun Yat-sen University Key Laboratory of Machine Intelligence and Advanced Computing, Sun Yat-sen University)

• CuCo: Graph Representation with Curriculum Contrastive Learning

  Guanyi Chu (Beijing University of Posts and Telecommunications)
  Xiao Wang (Beijing University of Posts and Telecommunications)
  Chuan Shi (Beijing University of Posts and Telecommunications)
  Xunqiang Jiang (Beijing University of Posts and Telecommunications)

• Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning

  Ming Jin (Monash University)
  Yizhen Zheng (Monash University)
  Yuan-Fang Li (Monash University)
  Chen Gong (Nanjing University of Science and Technology)
  Chuan Zhou (Chinese Academy of Sciences)
  Shirui Pan (Monash University)

sequence

• k-Nearest Neighbors by Means of Sequence to Sequence Deep Neural Networks and Memory Networks

  Yiming Xu (Northwestern University)
  Diego Klabjan (Northwestern University)

• A Novel Sequence-to-Subgraph Framework for Diagnosis Classification

  Jun Chen (Baidu Inc, Beijing 100193, China)
  Quan Yuan (Baidu Inc, Beijing 100193, China)
  Chao Lu (Baidu Inc, Beijing 100193, China)
  Haifeng Huang (Baidu Inc, Beijing 100193, China)

• Multi-series Time-aware Sequence Partitioning for Disease Progression Modeling

  Xi Yang (Department of Computer Science, North Carolina State University)
  Yuan Zhang (Department of Computer Science, North Carolina State University)
  Min Chi (Department of Computer Science, North Carolina State University)

Autoencoder

• Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness

  Dazhong Shen (School of Computer Science and Technology, University of Science and Technology of China Baidu Talent Intelligence Center)
  Chuan Qin (Baidu Talent Intelligence Center)
  Chao Wang (School of Computer Science and Technology, University of Science and Technology of China Baidu Talent Intelligence Center)
  Hengshu Zhu (Baidu Talent Intelligence Center)
  Enhong Chen (School of Computer Science and Technology, University of Science and Technology of China)
  Hui Xiong (Rutgers, The State University of New Jersey)

Recurrent Neural Network

• Change Matters: Medication Change Prediction with Recurrent Residual Networks

  Chaoqi Yang (University of Illinois at Urbana-Champaign)
  Cao Xiao (IQVIA)
  Lucas Glass (IQVIA)
  Jimeng Sun (University of Illinois at Urbana-Champaign)

• State-Based Recurrent SPMNs for Decision-Theoretic Planning under Partial Observability

  Layton Hayes (Institute for AI, University of Georgia, Athens GA 30602)
  Prashant Doshi (Institute for AI, University of Georgia, Athens GA 30602 Department of Computer Science, University of Georgia, Athens GA 30602)
  Swaraj Pawar (Dept. of Computer Science, University of Georgia, Athens GA 30602)
  Hari Teja Tatavarti (Institute for AI, University of Georgia, Athens GA 30602)

• Online Credit Payment Fraud Detection via Structure-Aware Hierarchical Recurrent Neural Network

  Wangli Lin (Alibaba Group, Hangzhou, China)
  Li Sun (Alibaba Group, Hangzhou, China)
  Qiwei Zhong (Alibaba Group, Hangzhou, China)
  Can Liu (Alibaba Group, Hangzhou, China)
  Jinghua Feng (Alibaba Group, Hangzhou, China)
  Xiang Ao (Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China)
  Hao Yang (Alibaba Group, Hangzhou, China)

causal analysis

• Causal Discovery with Multi-Domain LiNGAM for Latent Factors

  Yan Zeng (Guangdong University of Technology RIKEN)
  Shohei Shimizu (Shiga University RIKEN)
  Ruichu Cai (Guangdong University of Technology)
  Feng Xie (Peking University)
  Michio Yamamoto (Okayama University RIKEN)
  Zhifeng Hao (Guangdong University of Technology Foshan University)

• Inferring Time-delayed Causal Relations in POMDPs from the Principle of Independence of Cause and Mechanism

  Junchi Liang (Department of Computer Science, Rutgers University, New Jersey, USA)
  Abdeslam Boularias (Department of Computer Science, Rutgers University, New Jersey, USA)

• User Retention: A Causal Approach with Triple Task Modeling

  Yang Zhang (Ant Group Beihang University)
  Dong Wang (Ant Group)
  Qiang Li (Ant Group)
  Yue Shen (Ant Group)
  Ziqi Liu (Ant Group)
  Xiaodong Zeng (Ant Group)
  Zhiqiang Zhang (Ant Group)
  Jinjie Gu (Ant Group)
  Derek F. Wong (University of Macau)

• Ordering-Based Causal Discovery with Reinforcement Learning

  Xiaoqiang Wang (State Key Laboratory for Manufacturing Systems Engineering, School of Automation Science and Engineering, Xi’an Jiaotong University)
  Yali Du (University College London)
  Shengyu Zhu (Huawei Noah’s Ark Lab)
  Liangjun Ke (State Key Laboratory for Manufacturing Systems Engineering, School of Automation Science and Engineering, Xi’an Jiaotong University)
  Zhitang Chen (Huawei Noah’s Ark Lab)
  Jianye Hao (Huawei Noah’s Ark Lab College of Intelligence and Computing, Tianjin University)
  Jun Wang (University College London)

• Dependent Multi-Task Learning with Causal Intervention for Image Captioning

  Wenqing Chen (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University)
  Jidong Tian (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University)
  Caoyun Fan (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University)
  Hao He (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University)
  Yaohui Jin (MoE Key Lab of Artificial Intelligence, AI Institute, Shanghai Jiao Tong University State Key Lab of Advanced Optical Communication System and Network, Shanghai Jiao Tong University)

• Provable Guarantees on the Robustness of Decision Rules to Causal Interventions

  Benjie Wang (University of Oxford)
  Clare Lyle (University of Oxford)
  Marta Kwiatkowska (University of Oxford)

• A Ladder of Causal Distances

  Maxime Peyrard (EPFL)
  Robert West (EPFL)

correlation analysis (association analysis)

• Differentially Private Correlation Alignment for Domain Adaptation

  Kaizhong Jin (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China)
  Xiang Cheng (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China)
  Jiaxi Yang (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China)
  Kaiyuan Shen (State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China)

• Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction

  Guofeng Lv (SenseTime Research)
  Zhiqiang Hu (SenseTime Research)
  Yanguang Bi (SenseTime Research)
  Shaoting Zhang (SenseTime Research)

• Correlation-Guided Representation for Multi-Label Text Classification

Qian-Wen Zhang (Tencent Cloud Xiaowei, Beijing 100080, China)
Ximing Zhang (Beijing University of Posts and Telecommunications, Beijing 100876, China)
Zhao Yan (Tencent Cloud Xiaowei, Beijing 100080, China)
Ruifang Liu (Beijing University of Posts and Telecommunications, Beijing 100876, China)
Yunbo Cao (Tencent Cloud Xiaowei, Beijing 100080, China)
Min-Ling Zhang (School of Computer Science and Engineering, Southeast University, Nanjing 210096, China Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, China)

• Location Predicts You: Location Prediction via Bi-direction Speculation and Dual-level Association

  Xixi Li (National Engineering Research Center for Multimedia Software (NERCMS), School of Computer Science, Wuhan University)
  Ruimin Hu (National Engineering Research Center for Multimedia Software (NERCMS), School of Computer Science, Wuhan University)
  Zheng Wang (Research Institute for an Inclusive Society through Engineering (RIISE), The University of Tokyo Department of Information and Communication Engineering, The University of Tokyo)
  Toshihiko Yamasaki (Research Institute for an Inclusive Society through Engineering (RIISE), The University of Tokyo Department of Information and Communication Engineering, The University of Tokyo)

clustering

About distribution

missing value & irregularly sampled time series [Incomplete, imputation, …]

interpretable [Understanding, explanation, Attribution …]