Yufeng Zhan
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Selected Publications

Selected Conference Papers

  1. Tianyu Qi, Lei Xue, Yufeng Zhan, and Xiaobo Ma, "Sylva: Tailoring Personalized Adversarial Defense in Pre-trained Models via Collaborative Fine-tuning," ACM Conference on Computer and Communications Security, 2025.

  2. Tijin Yan, Hengheng Gong, Yongping He, Yufeng Zhan, and Yuanqing Xia, "Probabilistic Time Series Modeling with Decomposable Denoising Diffusion Model," International Conference on Machine Learning, 2024.

  3. Tianyu Qi, Yufeng Zhan, Peng Li, and Yuanqing Xia, "Tomtit: Hierarchical Federated Fine-Tuning of Giant Models based on Autonomous Synchronization," IEEE International Conference on Computer Communications, 2024.

  4. Yufeng Zhan and Jiang Zhang, "An Incentive Mechanism Design for Efficient Edge Learning by Deep Reinforcement Learning Approach," IEEE International Conference on Computer Communications, 2020.

  5. Yufeng Zhan, Peng Li, and Song Guo, "Experience-driven Computational Resource Allocation of Federated Learning by Deep Reinforcement Learning," IEEE International Parallel & Distributed Processing Symposium, 2020.

Selected Journal Papers

  1. Haosong Peng, Yufeng Zhan, Di-Hua Zhai, Xiaopu Zhang, and Yuanqing Xia "Egret: Reinforcement Mechanism for Sequential Computation Offloading in Edge Computing," IEEE Transactions on Service Computing, 2024.

  2. Yufeng Zhan, Peng Li, Leijie Wu, and Song Guo, "L4L: Experience-Driven Computational Resource Control in Federated Learning," IEEE Transactions on Computers, 2022.

  3. Yufeng Zhan, Song Guo, Peng Li, and Jiang Zhang, "A Deep Reinforcement Learning Based Offloading Game in Edge Computing," IEEE Transactions on Computers, 2020. (Best Paper Award)

  4. Yufeng Zhan, Peng Li, Zhihao Qu, Deze Zeng, and Song Guo, "A learning-based incentive mechanism for federated learning," IEEE Internet of Things Journal, 2020. (ESI Highly Cited Paper)

  5. Yufeng Zhan, Chi Harold Liu,Yinuo Zhao, Jiang Zhang, and Jian Tang, "Free Market of Multi-leader Multi-follower Mobile Crowdsensing: An Incentive Mechanism Design by Deep Reinforcement Learning," IEEE Transactions on Mobile Computing, 2020.

Book Chapter

  1. 夏元清,詹玉峰,孙立峰,刘驰,李云,翁健,李哲涛,赖李媛君. "大规模云数据中心智能管理技术及应用," 科学出版社, 2024. (国家科学技术学术著作出版基金资助著作)