1 citations · 1 across the 4 of their papers we have counts for
4 papers
FedUP: One-Shot Federated Unlearning via Centroid-Guided Plug-in Filters
Feihong Nan, Zhengyi Zhong, Pan Wang +4
Federated unlearning (FU) is critical for complying with legal mandates like the right to be forgotten in decentralized systems, yet current methods face a persistent dilemma betwe…
Make LLM Learn to Synthesize from Streaming Experiences through Feedback
Zhenlin Hu, Yan Wang, Zhen Bi +7
Large language models (LLMs) have been widely adopted for synthetic data generation, significantly reducing annotation costs. However, most existing studies treat synthesis as a se…
Multi-task Federated Learning with Encoder-Decoder Structure: Enabling Collaborative Learning Across Different Tasks
Jingxuan Zhou, Weidong Bao, Ji Wang +3
Federated learning has been extensively studied and applied due to its ability to ensure data security in distributed environments while building better models. However, clients pa…
FedHPD: Heterogeneous Federated Reinforcement Learning via Policy Distillation
Wenzheng Jiang, Ji Wang, Xiongtao Zhang +3
Federated Reinforcement Learning (FedRL) improves sample efficiency while preserving privacy; however, most existing studies assume homogeneous agents, limiting its applicability i…