most citedMulti-task Federated Learning with Encoder-Decoder Structure: Enabling Collaborative Learning Across Different Tasks

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

3 papers · 1 filter

cs.LG2026

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…

cs.LG2025★ 1 cited

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…

cs.LG2025

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…