Publications

^♮ indicates equal contribution, ^★ indicates interns / students I have advised.

• Interpreting Graph Neural Networks with In-Distributed Proxies
  Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mohan Mondal, Hua Wei, Dongsheng Luo
  Truestworthy Learning on Graphs Workshop at the Web Conference (TrustLOG @ WWW), 2024
  [arXiv]


• Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning
  Yizhou Zhang^★, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Haifeng Chen, Yan Liu
  Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2023
  


• Interdependent Causal Networks for Root Cause Localization
  Dongjie Wang, Zhengzhang Chen, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, Haifeng Chen
  Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2023 (ADS Track)
  [arXiv]


• Time Series Contrastive Learning with Information-Aware Augmentations
  D. Luo, W. Cheng, Y. Wang, D. Xu, Jingchao Ni, W. Yu, X. Zhang, Y. Liu, Y. Chen, H. Chen, X. Zhang
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2023
  [arXiv]


• Towards Robust Graph Neural Networks via Adversarial Contrastive Learning
  Shen Wang, Zhengzhang Chen, Jingchao Ni, Haifeng Chen, Philip S. Yu
  Proceedings of the IEEE International Conference on Big Data (BigData), 2022


• Towards Learning Disentangled Representations for Time Series
  Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Jingchao Ni, Denghui Zhang, Haifeng Chen, Xia Hu
  Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2022 (ADS Track)
  [arXiv]


• Superclass-Conditional Gaussian Mixture Model for Learning Fine-Grained Embeddings
  Jingchao Ni, Wei Cheng, Zhengzhang Chen, Takayoshi Asakura, Tomoya Soma, Sho Kato, Haifeng Chen
  The International Conference on Learning Representations (ICLR), 2022
  (Spotlight Presentation, 5%)
  [code]


• Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph
  Liyan Xu, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao, Jinho D. Choi
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2022


• Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization
  Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, Haifeng Chen
  Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2021


• Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
  Lei Cai, Zhengzhang Chen, Chen Luo, Jiaping Gui, Jingchao Ni, Ding Li, Haifeng Chen
  Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2021 (Applied Track)
  [code]


• Convolutional Transformer based Dual Discriminator General Adversarial Networks for Video Anomaly Detection
  Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen
  Proceedings of the ACM International Conference on Multimedia (MM), 2021


• Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection
  Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, Jiliang Tang
  Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2021 (ADS Track)


• Unsupervised Concept Representation Learning for Length-Varying Text Similarity
  Xuchao Zhang, Bo Zong, Wei Cheng, Jingchao Ni, Yanchi Liu, Haifeng Chen
  Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT), 2021


• FACESEC: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems
  Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, Yevgeniy Vorobeychik
  Proceedings of the Conference on Computer Vision and Pattern Recognition (CVPR), 2021
  [arXiv] [suppl] [code]


• Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection
  Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Haifeng Chen, Xiang Zhang
  Proceedings of the SIAM International Conference on Data Mining (SDM), 2021


• Dynamic Gaussian Mixture based Deep Generative Model for Robust Forecasting on Sparse Multivariate Time Series
  Yinjun Wu^★, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, Susan Davidson
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2021
  [arXiv] [code]


• Multi-Task Recurrent Modular Networks
  Dongkuan Xu, Wei Cheng, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2021


• Learning to Drop: Robust Graph Neural Network via Topological Denoising
  Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen, Xiang Zhang
  Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2021
  [arXiv]


• T2-Net: A Semi-supervised Deep Model for Turbulence Forecasting
  Denghui Zhang, Yanchi Liu, Wei Cheng, Bo Zong, Jingchao Ni, Zhengzhang Chen, Haifeng Chen, Hui Xiong
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2020


• Robust Graph Representation Learning via Neural Sparsification
  Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
  Proceedings of the International Conference on Machine Learning (ICML), 2020
  [suppl]


• Node Classification in Temporal Graphs Through Stochastic Sparsification and Temporal Structural Convolution
  Cheng Zheng, Bo Zong, Wei Cheng, Dongjin Song, Jingchao Ni, Wenchao Yu, Haifeng Chen, Wei Wang
  Proceedings of the ECML-PKDD, 2020


• Inductive and Unsupervised Representation Learning on Graph Structured Objects
  Lichen Wang, Bo Zong, Qianqian Ma, Wei Cheng, Jingchao Ni, Wenchao Yu, Yanchi Liu, Dongjin Song, Haifeng Chen, Yun Fu
  The International Conference on Learning Representations (ICLR), 2020


• Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-based Recommendation
  Xin Dong^★, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, Gerard de Melo
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2020
  [arXiv]


• Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval
  D. Zhu, D. Song, Y. Chen, C. Lumezanu, W. Cheng, B. Zong, Jingchao Ni, T. Mizoguchi, T. Yang, H. Chen
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2020


• Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series
  D. Xu, W. Cheng, B. Zong, D. Song, Jingchao Ni, W. Yu, Y. Liu, H. Chen, X. Zhang
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2020


• Deep Multi-Graph Clustering via Attentive Cross-Graph Association
  Dongsheng Luo^★, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu, Xiang Zhang
  Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), 2020
  [code]


• Adaptive Neural Network for Node Classification in Dynamic Networks
  Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2019


• Heterogeneous Graph Matching Networks for Unknown Malware Detection
  Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu
  Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019


• Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification
  S. Wang, Z. Chen, D. Li, Z. Li, L. Tang, Jingchao Ni, J. Rhee, H. Chen, P. S. Yu
  Proceedings of the SIAM International Conference on Data Mining (SDM), 2019


• Deep Co-Clustering
  D. Xu, W. Cheng, B. Zong, Jingchao Ni, D. Song, W. Yu, Y. Chen, H. Chen, X. Zhang
  Proceedings of the SIAM International Conference on Data Mining (SDM), 2019


• A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data
  C. Zhang, D. Song, Y. Chen, X. Feng, C. Lumezanu, W. Cheng, Jingchao Ni, B. Zong, H. Chen, N. Chawla
  Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2019
  [arXiv]


• Co-Regularized Deep Multi-Network Embedding
  Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang
  Proceedings of the International Conference on World Wide Web (WWW), 2018
  [code] [slides]


• The Multi-Walker Chain and Its Application in Local Community Detection
  Yuchen Bian, Jingchao Ni, Wei Cheng, Xiang Zhang
  Knowledge and Information Systems (KAIS), 2018
  (Best Papers of ICDM 2017)


• Local Graph Clustering by Multi-Network Random Walk with Restart
  Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Yu, John Yen, Xiang Zhang
  Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018


• ComClus: A Self-Grouping Framework for Multi-Network Clustering
  Jingchao Ni, Wei Cheng, Wei Fan, Xiang Zhang
  IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018


• Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems
  Jingchao Ni, Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017


• Automated Medical Diagnosis by Ranking Clusters Across the Symptom-Disease Network
  Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017


• Many Heads are Better than One: Local Community Detection by the Multi-Walker Chain
  Yuchen Bian, Jingchao Ni, Wei Cheng, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017
  (Best Paper Award Candidate)


• Cross-Network Clustering and Cluster Ranking for Medical Diagnosis
  Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2017 (Poster)


• Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamic Analysis on Vanishing Correlations
  Wei Cheng^♮, Jingchao Ni^♮, Kai Zhang, Haifeng Chen, Guofei Jiang, Yu Shi, Xiang Zhang, Wei Wang
  ACM Transactions on Knowledge Discovery from Data (TKDD), 2017


• Self-Grouping Multi-Network Clustering
  Jingchao Ni, Wei Cheng, Wei Fan, Xiang Zhang
  Proceedings of the IEEE International Conference on Data Mining (ICDM), 2016


• Disease Gene Prioritization by Integrating Tissue-Specific Molecular Networks Using a Robust Multi-Network Model
  Jingchao Ni, Mehmet Koyuturk, Hanghang Tong, Jonathan Haines, Rong Xu, Xiang Zhang
  BMC Bioinformatics, 2016
  [code]


• Flexible and Robust Multi-Network Clustering
  Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang
  Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2015
  [code] [slides] [poster]


• Inside the Atoms: Ranking on a Network of Networks
  Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang
  Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2014
  [code] [slides] [poster]