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ORCIDZhiyuan Wang 0002
Person information
- affiliation: University of Science and Technology of China (USTC), School of Computer Science, Suzhou, Jiangsu, China
Other persons with the same name
- Zhiyuan Wang — disambiguation page
- Zhiyuan Wang 0001
![[0000-0001-7867-7626]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0001-7867-7626")
— DigiPen Institute of Technology Singapore, Department of Computer Science, Singapore (and 1 more) - Zhiyuan Wang 0003 — University of Virginia, Charlottesville, VA, USA
- Zhiyuan Wang 0004 — Beihang University, Beijing, China
- Zhiyuan Wang 0005 — Southwest Petroleum University, Chengdu, Sichuan, China
- Zhiyuan Wang 0006 — University of Electronic Science and Technology of China, China
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2020 – today
- 2025
[j16]Zhenguo Ma, Huaqing Tu, Li Zhou, Pengli Ji, Xiaoran Yan, Hongli Xu, Zhiyuan Wang, Suo Chen:
Hier-FUN: Hierarchical Federated Learning and Unlearning in Heterogeneous Edge Computing. IEEE Internet Things J. 12(7): 8653-8668 (2025)- [j15]Yang Xu, Yunming Liao, Hongli Xu, Zhiyuan Wang, Lun Wang, Jianchun Liu, Chen Qian:
FedSNN: Training Slimmable Neural Network With Federated Learning in Edge Computing. IEEE Trans. Netw. 33(1): 414-429 (2025) - [j14]Yang Xu, Ying Zhu, Zhiyuan Wang, Hongli Xu, Yunming Liao:
Enhancing Federated Learning Through Layer-Wise Aggregation Over Non-IID Data. IEEE Trans. Serv. Comput. 18(2): 798-811 (2025) - 2024
- [j13]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Jianchun Liu, Chen Qian, Chunming Qiao:
Computation and Communication Efficient Federated Learning With Adaptive Model Pruning. IEEE Trans. Mob. Comput. 23(3): 2003-2021 (2024) - [j12]Yang Xu, Lun Wang, Hongli Xu, Jianchun Liu, Zhiyuan Wang, Liusheng Huang:
Enhancing Federated Learning With Server-Side Unlabeled Data by Adaptive Client and Data Selection. IEEE Trans. Mob. Comput. 23(4): 2813-2831 (2024) - [j11]Yang Xu, Zhida Jiang, Hongli Xu, Zhiyuan Wang, Chen Qian, Chunming Qiao:
Federated Learning With Client Selection and Gradient Compression in Heterogeneous Edge Systems. IEEE Trans. Mob. Comput. 23(5): 5446-5461 (2024) - [j10]Jianchun Liu, Jiaming Yan, Hongli Xu, Zhiyuan Wang, Jinyang Huang, Yang Xu:
Finch: Enhancing Federated Learning With Hierarchical Neural Architecture Search. IEEE Trans. Mob. Comput. 23(5): 6012-6026 (2024) - [j9]Suo Chen, Yang Xu, Hongli Xu, Zhenguo Ma, Zhiyuan Wang:
Enhancing Decentralized and Personalized Federated Learning With Topology Construction. IEEE Trans. Mob. Comput. 23(10): 9692-9707 (2024) - [j8]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Jianchun Liu, Chunming Qiao:
Semi-Supervised Decentralized Machine Learning With Device-to-Device Cooperation. IEEE Trans. Mob. Comput. 23(10): 9757-9771 (2024) - [j7]Jiaming Yan, Jianchun Liu, Hongli Xu, Zhiyuan Wang, Chunming Qiao:
Peaches: Personalized Federated Learning With Neural Architecture Search in Edge Computing. IEEE Trans. Mob. Comput. 23(11): 10296-10312 (2024) - [j6]Jianchun Liu, Qingmin Zeng, Hongli Xu, Yang Xu, Zhiyuan Wang, He Huang:
Adaptive Block-Wise Regularization and Knowledge Distillation for Enhancing Federated Learning. IEEE/ACM Trans. Netw. 32(1): 791-805 (2024) - [j5]Jun Liu, Jianchun Liu, Hongli Xu, Yunming Liao, Zhiyuan Wang, Qianpiao Ma:
YOGA: Adaptive Layer-Wise Model Aggregation for Decentralized Federated Learning. IEEE/ACM Trans. Netw. 32(2): 1768-1780 (2024) - [j4]Zhiyuan Wang, Hongli Xu, Yang Xu, Zhida Jiang, Jianchun Liu, Suo Chen:
FAST: Enhancing Federated Learning Through Adaptive Data Sampling and Local Training. IEEE Trans. Parallel Distributed Syst. 35(2): 221-236 (2024) - [c9]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Chunming Qiao:
Clients Help Clients: Alternating Collaboration for Semi-Supervised Federated Learning. ICDE 2024: 1847-1860 - 2023
- [j3]Zhiyuan Wang, Hongli Xu, Yang Xu, Zhida Jiang, Jianchun Liu:
CoopFL: Accelerating federated learning with DNN partitioning and offloading in heterogeneous edge computing. Comput. Networks 220: 109490 (2023) - [j2]Zhiyuan Wang, Hongli Xu, Jianchun Liu, Yang Xu, He Huang, Yangming Zhao:
Accelerating Federated Learning With Cluster Construction and Hierarchical Aggregation. IEEE Trans. Mob. Comput. 22(7): 3805-3822 (2023) - [c8]Suo Chen, Zhenguo Ma, Zhiyuan Wang:
Accelerating Hierarchical Federated Learning with Adaptive Aggregation Frequency in Edge Computing. CNIOT 2023: 990-995 - [c7]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Chen Qian:
Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression. INFOCOM 2023: 1-10 - [c6]Qingmin Zeng, Jianchun Liu, Hongli Xu, Zhiyuan Wang, Yang Xu, Yangming Zhao:
Enhanced Federated Learning with Adaptive Block-wise Regularization and Knowledge Distillation. IWQoS 2023: 1-4 - [i2]Zhipeng Sun, Yang Xu, Hongli Xu, Zhiyuan Wang:
Efficient Semi-Supervised Federated Learning for Heterogeneous Participants. CoRR abs/2307.15870 (2023) - 2022
- [c5]Lun Wang, Yang Xu, Hongli Xu, Jianchun Liu, Zhiyuan Wang, Liusheng Huang:
Enhancing Federated Learning with In-Cloud Unlabeled Data. ICDE 2022: 136-149 - [c4]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Chunming Qiao, Yangming Zhao:
FedMP: Federated Learning through Adaptive Model Pruning in Heterogeneous Edge Computing. ICDE 2022: 767-779 - [c3]Jianchun Liu, Yang Xu, Hongli Xu, Yunming Liao, Zhiyuan Wang, He Huang:
Enhancing Federated Learning with Intelligent Model Migration in Heterogeneous Edge Computing. ICDE 2022: 1586-1597 - [i1]Zhida Jiang, Yang Xu, Hongli Xu, Zhiyuan Wang, Chen Qian:
Adaptive Control of Client Selection and Gradient Compression for Efficient Federated Learning. CoRR abs/2212.09483 (2022) - 2021
- [j1]Jianchun Liu, Hongli Xu, Yang Xu, Zhenguo Ma, Zhiyuan Wang, Chen Qian, He Huang:
Communication-efficient asynchronous federated learning in resource-constrained edge computing. Comput. Networks 199: 108429 (2021) - [c2]Zhiyuan Wang, Hongli Xu, Jianchun Liu, He Huang, Chunming Qiao, Yangming Zhao:
Resource-Efficient Federated Learning with Hierarchical Aggregation in Edge Computing. INFOCOM 2021: 1-10 - [c1]Chao Li, Hongli Xu, Yang Xu, Zhiyuan Wang, Liusheng Huang:
DNN Inference Acceleration with Partitioning and Early Exiting in Edge Computing. WASA (1) 2021: 465-478
Coauthor Index
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