MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems. - Dewei Liu; Chuan He; Xin Peng 001; Fan Lin; Chenxi Zhang 003; Shengfang Gong; Ziang Li; Jiayu Ou; Zheshun Wu (ICSE (SEIP), 2021)

A Privacy-Preserved Online Personalized Federated Learning Framework for Indoor Localization. - Zheshun Wu; Xiaoping Wu; Xiaoli Long; Yunliang Long (SMC, 2021)

Multi-Level Federated Graph Learning and Self-Attention Based Personalized Wi-Fi Indoor Fingerprint Localization. - Zheshun Wu; Xiaoping Wu; Yunliang Long (IEEE Commun. Lett., 2022)

Dynamic Graph Neural Networks-Based Alert Link Prediction for Online Service Systems. - Yiru Chen; Chenxi Zhang 003; Zhen Dong; Dingyu Yang; Xin Peng 001; Jiayu Ou; Hong Yang; Zheshun Wu; Xiaojun Qu; Wei Li (ASE, 2023)

Federated Generalization via Information-Theoretic Distribution Diversification. - Zheshun Wu; Zenglin Xu; Dun Zeng; Qifan Wang 001 (CoRR, 2023)

Joint Scheduling and Robust Aggregation for Federated Localization Over Unreliable Wireless D2D Networks. - Zheshun Wu; Xiaoping Wu; Yunliang Long (IEEE Trans. Netw. Serv. Manag., 2023)

On the Necessity of Collaboration for Online Model Selection with Decentralized Data. - Junfan Li; Zheshun Wu; Zenglin Xu; Irwin King (NeurIPS, 2024)

Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives. - Yiyuan Yang; Zheshun Wu; Yong Chu; Zhenghua Chen; Zenglin Xu; Qingsong Wen (CoRR, 2024)

Online Optimization for Learning to Communicate over Time-Correlated Channels. - Zheshun Wu; Junfan Li; Zenglin Xu; Sumei Sun; Jie Liu 001 (CoRR, 2024)

Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization. - Dun Zeng; Zheshun Wu; Shiyu Liu; Yu Pan 005; Xiaoying Tang 002; Zenglin Xu (CoRR, 2024)

Information-Theoretic Generalization Analysis for Topology-Aware Heterogeneous Federated Edge Learning Over Noisy Channels. - Zheshun Wu; Zenglin Xu; Hongfang Yu; Jie Liu 001 (IEEE Signal Process. Lett., 2024)

Topology Learning for Heterogeneous Decentralized Federated Learning Over Unreliable D2D Networks. - Zheshun Wu; Zenglin Xu; Dun Zeng; Junfan Li; Jie Liu 001 (IEEE Trans. Veh. Technol., 2024)

Advocating for the Silent: Enhancing Federated Generalization for Nonparticipating Clients. - Zheshun Wu; Zenglin Xu; Dun Zeng; Qifan Wang 001; Jie Liu 001 (IEEE Trans. Neural Networks Learn. Syst., 2025)