Jingchao Ni

发表

Personalized Federated Learning via Heterogeneous Modular Networks

Wei Cheng, Wenchao Yu, Xiang Zhang, 2022, ArXiv.

Learning to Drop: Robust Graph Neural Network via Topological Denoising pdf

Bo Zong, Xiang Zhang, Wei Cheng, 2020, WSDM.

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

Xiang Zhang, Wei Fan, Jingchao Ni, 2018, IEEE Transactions on Knowledge and Data Engineering.

Self-Grouping Multi-network Clustering

Wei Cheng, Xiang Zhang, Wei Fan, 2016, 2016 IEEE 16th International Conference on Data Mining (ICDM).

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

Hanghang Tong, Xiang Zhang, Mehmet Koyutürk, 2016, BMC Bioinformatics.

Robust Graph Representation Learning via Neural Sparsification

Bo Zong, Haifeng Chen, Cheng Zheng, 2020, ICML.

Flexible and Robust Multi-Network Clustering

Hanghang Tong, Wei Fan, Xiang Zhang, 2015, KDD.

Inside the atoms: ranking on a network of networks

Hanghang Tong, Wei Fan, Xiang Zhang, 2014, KDD.

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

Wei Cheng, Xiang Zhang, Yuchen Bian, 2018, Knowledge and Information Systems.

Local Graph Clustering by Multi-network Random Walk with Restart

John Yen, Xiang Zhang, Dongsheng Luo, 2018, PAKDD.

Co-Regularized Deep Multi-Network Embedding

Xiao Liu, Wei Cheng, Shiyu Chang, 2018, WWW.

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

Bo Zong, Nitesh V. Chawla, Wei Cheng, 2018, AAAI.

Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification

Philip S. Yu, Haifeng Chen, Zhengzhang Chen, 2018, SDM.

Multi-Task Recurrent Modular Networks

Wei Cheng, Bo Zong, Wenchao Yu, 2021, AAAI.

Deep Co-Clustering

Bo Zong, Yuncong Chen, Jingchao Ni, 2019, SDM.

Heterogeneous Graph Matching Networks for Unknown Malware Detection

Philip S. Yu, Haifeng Chen, Zhengzhang Chen, 2019, IJCAI.

Adversarial Defense Framework for Graph Neural Network pdf

Philip S. Yu, Xiao Yu, Haifeng Chen, 2019, ArXiv.

Personalized Federated Learning via Heterogeneous Modular Networks

Wei Cheng, Wenchao Yu, Xiang Zhang, 2022, 2022 IEEE International Conference on Data Mining (ICDM).

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection pdf

Zhiwei Wang, Haifeng Chen, Jiliang Tang, 2020, KDD.

FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems

Wei Cheng, Yevgeniy Vorobeychik, Jingchao Ni, 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series pdf

Bo Zong, Yanchi Liu, Yinjun Wu, 2021, AAAI.

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

Xinyang Feng, Jingchao Ni, Dongjin Song, 2021, ACM Multimedia.

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

Wei Cheng, Yuchen Bian, Jingchao Ni, 2018, Knowledge and Information Systems.

Many Heads are Better than One: Local Community Detection by the Multi-walker Chain

Wei Cheng, Xiang Zhang, Yuchen Bian, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation

Bo Zong, Yanchi Liu, Gerard de Melo, 2019, AAAI.

Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems

Wei Cheng, Haifeng Chen, Xiang Zhang, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

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

Bo Zong, Jingchao Ni, Wei Cheng, 2021, ArXiv.

Deep Multi-Graph Clustering via Attentive Cross-Graph Association

Suhang Wang, Yuchen Bian, Xiong Yu, 2020, WSDM.

Towards Learning Disentangled Representations for Time Series

Mengnan Du, D. Zha, Haifeng Chen, 2022, KDD.

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

Wei Cheng, Haifeng Chen, T. Asakura, 2022, ICLR.

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs pdf

Haifeng Chen, Zhengzhang Chen, Ding Li, 2020, CIKM.

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization

Bo Zong, Yanchi Liu, Jingchao Ni, 2021, CIKM.

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

Bo Zong, Yanchi Liu, Wenchao Yu, 2020, AAAI.

Inductive and Unsupervised Representation Learning on Graph Structured Objects

Bo Zong, Yanchi Liu, Haifeng Chen, 2020, ICLR.

Towards Robust Graph Neural Networks via Adversarial Contrastive Learning

Haifeng Chen, Zhengzhang Chen, Jingchao Ni, 2022, 2022 IEEE International Conference on Big Data (Big Data).

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-Sentence Dependency Graph pdf

Bo Zong, Yanchi Liu, Jinho D. Choi, 2021, AAAI.

Unsupervised Concept Representation Learning for Length-Varying Text Similarity

Wei Cheng, Bo Zong, Yanchi Liu, 2021, NAACL.

Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization

Zheng Wang, Yanjie Fu, Liang Tong, 2023, ArXiv.

Adaptive Neural Network for Node Classification in Dynamic Networks

Bo Zong, Xiang Zhang, Haifeng Chen, 2019, 2019 IEEE International Conference on Data Mining (ICDM).

Time Series Contrastive Learning with Information-Aware Augmentations

Wei Cheng, Yanchi Liu, Wenchao Yu, 2023, AAAI.

Unsupervised Document Embedding via Contrastive Augmentation pdf

Wei Cheng, Bo Zong, Yanchi Liu, 2021, ArXiv.

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

Xiang Zhang, Hongliang Fei, Wei Fan, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

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

Wei Cheng, Yu Shi, Wei Wang, 2017, ACM Trans. Knowl. Discov. Data.

Heterogeneous Graph Matching Networks pdf

Philip S. Yu, Haifeng Chen, Zhengzhang Chen, 2019, ArXiv.

Towards Learning Disentangled Representations for Time Series

Mengnan Du, D. Zha, Haifeng Chen, 2022, KDD.