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ORCIDZheshun Wu
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2020 – today
- 2025
[j6]Zheshun Wu
, Zenglin Xu, Dun Zeng, Qifan Wang, Jie Liu:
Advocating for the Silent: Enhancing Federated Generalization for Nonparticipating Clients. IEEE Trans. Neural Networks Learn. Syst. 36(8): 14174-14188 (2025)- [j5]Junlin Liu, Mengyu Yao, Shaofei Li, Dingyu Yang, Zheshun Wu, Xiaojun Qu, Ziqi Zhang, Ding Li, Yao Guo, Xiangqun Chen:
Not All Exceptions Are Created Equal: Triaging Error Logs in Real-World Enterprises. ACM Trans. Softw. Eng. Methodol. 34(8): 221:1-221:28 (2025) - 2024
- [j4]Zheshun Wu, Zenglin Xu, Hongfang Yu, Jie Liu:
Information-Theoretic Generalization Analysis for Topology-Aware Heterogeneous Federated Edge Learning Over Noisy Channels. IEEE Signal Process. Lett. 31: 691-695 (2024) - [j3]Zheshun Wu, Zenglin Xu, Dun Zeng, Junfan Li, Jie Liu:
Topology Learning for Heterogeneous Decentralized Federated Learning Over Unreliable D2D Networks. IEEE Trans. Veh. Technol. 73(8): 12201-12206 (2024) - [c4]Junfan Li, Zheshun Wu, Zenglin Xu, Irwin King:
On the Necessity of Collaboration for Online Model Selection with Decentralized Data. NeurIPS 2024 - [i8]Junfan Li, Zenglin Xu, Zheshun Wu, Irwin King:
On the Necessity of Collaboration in Online Model Selection with Decentralized Data. CoRR abs/2404.09494 (2024) - [i7]Yiyuan Yang, Zheshun Wu, Yong Chu, Zhenghua Chen, Zenglin Xu, Qingsong Wen:
Intelligent Cross-Organizational Process Mining: A Survey and New Perspectives. CoRR abs/2407.11280 (2024) - [i6]Zheshun Wu, Junfan Li, Zenglin Xu, Sumei Sun, Jie Liu:
Online Optimization for Learning to Communicate over Time-Correlated Channels. CoRR abs/2409.00575 (2024) - [i5]Dun Zeng, Zheshun Wu, Shiyu Liu, Yu Pan, Xiaoying Tang, Zenglin Xu:
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization. CoRR abs/2411.16303 (2024) - 2023
- [j2]Zheshun Wu, Xiaoping Wu, Yunliang Long:
Joint Scheduling and Robust Aggregation for Federated Localization Over Unreliable Wireless D2D Networks. IEEE Trans. Netw. Serv. Manag. 20(3): 3359-3379 (2023) - [c3]Yiru Chen, Chenxi Zhang, Zhen Dong, Dingyu Yang, Xin Peng, Jiayu Ou, Hong Yang, Zheshun Wu, Xiaojun Qu, Wei Li:
Dynamic Graph Neural Networks-Based Alert Link Prediction for Online Service Systems. ASE 2023: 79-90 - [i4]Zheshun Wu, Zenglin Xu, Dun Zeng, Qifan Wang:
Federated Generalization via Information-Theoretic Distribution Diversification. CoRR abs/2310.07171 (2023) - [i3]Zheshun Wu, Zenglin Xu, Hongfang Yu, Jie Liu:
Information-Theoretic Generalization Analysis for Topology-aware Heterogeneous Federated Edge Learning over Noisy Channels. CoRR abs/2310.16407 (2023) - [i2]Zheshun Wu, Zenglin Xu, Dun Zeng, Junfan Li, Jie Liu:
Topology Learning for Heterogeneous Decentralized Federated Learning over Unreliable D2D Networks. CoRR abs/2312.13611 (2023) - 2022
- [j1]Zheshun Wu, Xiaoping Wu, Yunliang Long:
Multi-Level Federated Graph Learning and Self-Attention Based Personalized Wi-Fi Indoor Fingerprint Localization. IEEE Commun. Lett. 26(8): 1794-1798 (2022) - 2021
- [c2]Dewei Liu, Chuan He, Xin Peng, Fan Lin, Chenxi Zhang, Shengfang Gong, Ziang Li, Jiayu Ou, Zheshun Wu:
MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems. ICSE (SEIP) 2021: 338-347 - [c1]Zheshun Wu, Xiaoping Wu, Xiaoli Long, Yunliang Long:
A Privacy-Preserved Online Personalized Federated Learning Framework for Indoor Localization. SMC 2021: 2834-2839 - [i1]Dewei Liu, Chuan He, Xin Peng, Fan Lin, Chenxi Zhang, Shengfang Gong, Ziang Li, Jiayu Ou, Zheshun Wu:
MicroHECL: High-Efficient Root Cause Localization in Large-Scale Microservice Systems. CoRR abs/2103.01782 (2021)
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