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ORCIDKun Yang 0011
Person information
- affiliation: University of Virginia, Charles L. Brown Department of Electrical and Computer Engineering, Charlottesville, VA, USA
Other persons with the same name
- Kun Yang — disambiguation page
- Kun Yang 0001
![[0000-0002-6782-6689]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0002-6782-6689")
— University of Electronic Science and Technology of China, School of Information and Communication Engineering, Chengdu, China (and 3 more) - Kun Yang 0002 — Hangzhou Dianzi University, College of Computer Science, Hangzhou, China (and 1 more)
- Kun Yang 0003 — Johns Hopkins School of Medicine, Department of Psychiatry and Behavioral Sciences, Baltimore, MD, USA (and 3 more)
- Kun Yang 0004 — Chinese Academy of Sciences, Institute of Tibetan Plateau Research, Beijing, China
- Kun Yang 0005 — Beijing University of Posts and Telecommunications, School of Information and Communication Engineering, China
- Kun Yang 0006 — Peking University, College of Engineering, Center for Applied Physics and Technology, Beijing, China
- Kun Yang 0007 — Yunnan Normal University, School of information Science and Technology, Kunming, China
- Kun Yang 0008 — Super Radio AS Oslo, Norway (and 1 more)
- Kun Yang 0009 — Beijing University of Technology, Faculty of Information Technology, China
- Kun Yang 0010 — Fudan University, Academy for Engineering and Technology, Shanghai, China (and 1 more)
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2020 – today
- 2024
[i5]Chengshuai Shi, Kun Yang, Jing Yang, Cong Shen:
Best Arm Identification for Prompt Learning under a Limited Budget. CoRR abs/2402.09723 (2024)- 2023
- [j1]Kun Yang, Shengbo Chen, Cong Shen:
On the Convergence of Hybrid Server-Clients Collaborative Training. IEEE J. Sel. Areas Commun. 41(3): 802-819 (2023) - [c5]Kun Yang, Cong Shen, Jing Yang, Shu-Ping Yeh, Jerry Sydir:
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets. ACSSC 2023: 629-633 - [c4]Kun Yang, Chengshuai Shi, Cong Shen:
Teaching Reinforcement Learning Agents via Reinforcement Learning. CISS 2023: 1-6 - [i4]Jieming Bian, Lei Wang, Kun Yang, Cong Shen, Jie Xu:
Accelerating Hybrid Federated Learning Convergence under Partial Participation. CoRR abs/2304.05397 (2023) - [i3]Kun Yang, Cong Shen, Jing Yang, Shu-Ping Yeh, Jerry Sydir:
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets. CoRR abs/2311.11423 (2023) - [i2]Kun Yang, Shu-Ping Yeh, Menglei Zhang, Jerry Sydir, Jing Yang, Cong Shen:
Advancing RAN Slicing with Offline Reinforcement Learning. CoRR abs/2312.10547 (2023) - [i1]Chengshuai Shi, Ruida Zhou, Kun Yang, Cong Shen:
Harnessing the Power of Federated Learning in Federated Contextual Bandits. CoRR abs/2312.16341 (2023) - 2022
- [c3]Kun Yang, Donghao Li, Cong Shen, Jing Yang, Shu-Ping Yeh, Jerry Sydir:
Multi-Agent Reinforcement Learning for Wireless User Scheduling: Performance, Scalablility, and Generalization. IEEECONF 2022: 1169-1174 - [c2]Kun Yang, Cong Shen:
On the Convergence of Hybrid Federated Learning with Server-Clients Collaborative Training. CISS 2022: 252-257 - 2020
- [c1]Kun Yang, Cong Shen, Tie Liu:
Deep Reinforcement Learning based Wireless Network Optimization: A Comparative Study. INFOCOM Workshops 2020: 1248-1253
Coauthor Index
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