pFedMoE: Data-Level Personalization with Mixture of Experts for
Model-Heterogeneous Personalized Federated Learning

pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning

2 February 2024

Heng-Ming Zhang

Papers citing "pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning"

18 / 18 papers shown

Title
FedGH: Heterogeneous Federated Learning with Generalized Global Header Liping Yi Gang Wang Xiaoguang Liu Zhuan Shi Han Yu FedML 102 78 0 23 Mar 2023
FedClassAvg: Local Representation Learning for Personalized Federated Learning on Heterogeneous Neural Networks Jaehee Jang Heonseok Ha Dahuin Jung Sungroh Yoon FedML 83 41 0 25 Oct 2022
Fed2: Feature-Aligned Federated Learning Fuxun Yu Weishan Zhang Zhuwei Qin Zirui Xu Di Wang Chenchen Liu Zhi Tian Xiang Chen FedML 70 76 0 28 Nov 2021
FedGEMS: Federated Learning of Larger Server Models via Selective Knowledge Fusion Sijie Cheng Jingwen Wu Yanghua Xiao Yang Liu Yang Liu FedML 46 68 0 21 Oct 2021
FedZKT: Zero-Shot Knowledge Transfer towards Resource-Constrained Federated Learning with Heterogeneous On-Device Models Lan Zhang Dapeng Wu Xiaoyong Yuan FedML 60 48 0 08 Sep 2021
FedKD: Communication Efficient Federated Learning via Knowledge Distillation Chuhan Wu Fangzhao Wu Lingjuan Lyu Yongfeng Huang Xing Xie FedML 75 388 0 30 Aug 2021
Federated Mixture of Experts M. Reisser Christos Louizos E. Gavves Max Welling FedML 71 24 0 14 Jul 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 80 658 0 20 May 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts Binbin Guo Yuan Mei Danyang Xiao Weigang Wu Ye Yin Hongli Chang MoE 85 22 0 31 Dec 2020
Specialized federated learning using a mixture of experts Edvin Listo Zec Olof Mogren John Martinsson L. R. Sütfeld D. Gillblad FedML 57 29 0 05 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 96 556 0 03 Oct 2020
Multi-site fMRI Analysis Using Privacy-preserving Federated Learning and Domain Adaptation: ABIDE Results Xiaoxiao Li Yufeng Gu Nicha Dvornek Lawrence H. Staib P. Ventola James S. Duncan FedML OOD 76 354 0 16 Jan 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 117 562 0 06 Jan 2020
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer Hong Chang Virat Shejwalkar Reza Shokri Amir Houmansadr FedML 77 168 0 24 Dec 2019
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 256 6,261 0 10 Dec 2019
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 95 854 0 08 Oct 2019
Differentiable Learning-to-Normalize via Switchable Normalization Ping Luo Jiamin Ren Zhanglin Peng Ruimao Zhang Jingyu Li 51 177 0 28 Jun 2018
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,486 0 17 Feb 2016