Jingchao Ni

According to our database, Jingchao Ni authored at least 54 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Explanation-Preserving Augmentation for Semi-Supervised Graph Representation Learning.

Zhuomin Chen, Jingchao Ni, Hojat Allah Salehi, Xu Zheng, Esteban Schafir, Farhad Shirani, Dongsheng Luo

CoRR, 2024

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

CoRR, 2024

MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series.

Jingchao Ni, Gauthier Guinet, Peihong Jiang, Laurent Callot, Andrey Kan

CoRR, 2024

Generating In-Distribution Proxy Graphs for Explaining Graph Neural Networks.

Zhuomin Chen, Jiaxing Zhang, Jingchao Ni, Xiaoting Li, Yuchen Bian, Md Mezbahul Islam, Ananda Mondal, Hua Wei, Dongsheng Luo

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization.

Dongjie Wang, Zhengzhang Chen, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, Haifeng Chen

CoRR, 2023

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 Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Time Series Contrastive Learning with Information-Aware Augmentations.

Dongsheng Luo, Wei Cheng, Yingheng Wang, Dongkuan Xu, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Yanchi Liu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

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 KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings.

Jingchao Ni, Wei Cheng, Zhengzhang Chen, Takayoshi Asakura, Tomoya Soma, Sho Kato, Haifeng Chen

Proceedings of the Tenth International Conference on Learning Representations, 2022

Personalized Federated Learning via Heterogeneous Modular Networks.

Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, Xiang Zhang

Proceedings of the IEEE International Conference on Data Mining, 2022

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, 2022

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 Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages?

Junxiang Wang, Xuchao Zhang, Bo Zong, Yanchi Liu, Wei Cheng, Jingchao Ni, Haifeng Chen, Liang Zhao

CoRR, 2021

Unsupervised Document Embedding via Contrastive Augmentation.

Dongsheng Luo, Wei Cheng, Jingchao Ni, Wenchao Yu, Xuchao Zhang, Bo Zong, Yanchi Liu, Zhengzhang Chen, Dongjin Song, Haifeng Chen, Xiang Zhang

CoRR, 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 WSDM '21, 2021

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 2021 SIAM International Conference on Data Mining, 2021

Unsupervised Concept Representation Learning for Length-Varying Text Similarity.

Xuchao Zhang, Bo Zong, Wei Cheng, Jingchao Ni, Yanchi Liu, Haifeng Chen

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection.

Xinyang Feng, Dongjin Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, Haifeng Chen

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 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 KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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 IEEE Conference on Computer Vision and Pattern Recognition, 2021

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 CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 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 CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Multi-Task Recurrent Modular Networks.

Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 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 B. Davidson

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Deep Multi-Graph Clustering via Attentive Cross-Graph Association.

Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Bill Yu, Xiang Zhang

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

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 Machine Learning and Knowledge Discovery in Databases, 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 37th International Conference on Machine Learning, 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

Proceedings of the 8th International Conference on Learning Representations, 2020

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 20th IEEE International Conference on Data Mining, 2020

Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval.

Dixian Zhu, Dongjin Song, Yuncong Chen, Cristian Lumezanu, Wei Cheng, Bo Zong, Jingchao Ni, Takehiko Mizoguchi, Tianbao Yang, Haifeng Chen

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series.

Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 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 Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

The multi-walker chain and its application in local community detection.

Yuchen Bian, Jingchao Ni, Wei Cheng, Xiang Zhang

Knowl. Inf. Syst., 2019

Heterogeneous Graph Matching Networks.

Shen Wang, Zhengzhang Chen, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, Philip S. Yu

CoRR, 2019

Adversarial Defense Framework for Graph Neural Network.

Shen Wang, Zhengzhang Chen, Jingchao Ni, Xiao Yu, Zhichun Li, Haifeng Chen, Philip S. Yu

CoRR, 2019

Deep Co-Clustering.

Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Yuncong Chen, Haifeng Chen, Xiang Zhang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification.

Shen Wang, Zhengzhang Chen, Ding Li, Zhichun Li, Lu-An Tang, Jingchao Ni, Junghwan Rhee, Haifeng Chen, Philip S. Yu

Proceedings of the 2019 SIAM International Conference on Data Mining, 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 Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

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 2019 IEEE International Conference on Data Mining, 2019

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.

Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, Nitesh V. Chawla

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

ComClus: A Self-Grouping Framework for Multi-Network Clustering.

Jingchao Ni, Wei Cheng, Wei Fan, Xiang Zhang

IEEE Trans. Knowl. Data Eng., 2018

Deep Program Reidentification: A Graph Neural Network Solution.

Shen Wang, Zhengzhang Chen, Ding Li, Lu-An Tang, Jingchao Ni, Zhichun Li, Junghwan Rhee, Haifeng Chen, Philip S. Yu

CoRR, 2018

Co-Regularized Deep Multi-Network Embedding.

Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang

Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Local Graph Clustering by Multi-network Random Walk with Restart.

Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Bill Yu, John Yen, Xiang Zhang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

2017

Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations.

Wei Cheng, Jingchao Ni, Kai Zhang, Haifeng Chen, Guofei Jiang, Yu Shi, Xiang Zhang, Wei Wang

ACM Trans. Knowl. Discov. Data, 2017

Automated Medical Diagnosis by Ranking Clusters Across the Symptom-Disease Network.

Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

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 2017 IEEE International Conference on Data Mining, 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 2017 IEEE International Conference on Data Mining, 2017

Cross-Network Clustering and Cluster Ranking for Medical Diagnosis.

Jingchao Ni, Hongliang Fei, Wei Fan, Xiang Zhang

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

2016

Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.

Jingchao Ni, Mehmet Koyutürk, Hanghang Tong, Jonathan L. Haines, Rong Xu, Xiang Zhang

BMC Bioinform., 2016

Self-Grouping Multi-network Clustering.

Jingchao Ni, Wei Cheng, Wei Fan, Xiang Zhang

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015

Flexible and Robust Multi-Network Clustering.

Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014

Inside the atoms: ranking on a network of networks.

Jingchao Ni, Hanghang Tong, Wei Fan, Xiang Zhang

Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014