FedL2P: Federated Learning to Personalize

FedL2P: Federated Learning to Personalize

3 October 2023

Royson Lee

Timothy M. Hospedales

Nicholas D. Lane

Papers citing "FedL2P: Federated Learning to Personalize"

7 / 7 papers shown

Title
FedDAR: Federated Domain-Aware Representation Learning Aoxiao Zhong Hao He Zhaolin Ren Na Li Quanzheng Li OOD AI4CE 29 9 0 08 Sep 2022
Evaluation of Hyperparameter-Optimization Approaches in an Industrial Federated Learning System Stephan Holly Thomas Hiessl Safoura Rezapour Lakani Daniel Schall C. Heitzinger J. Kemnitz FedML 34 17 0 15 Oct 2021
FedMe: Federated Learning via Model Exchange Koji Matsuda Yuya Sasaki Chuan Xiao Makoto Onizuka FedML 45 19 0 15 Oct 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 181 267 0 26 Feb 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 787 0 15 Feb 2021
Adaptive Personalized Federated Learning Yuyang Deng Mohammad Mahdi Kamani M. Mahdavi FedML 212 542 0 30 Mar 2020
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 329 11,681 0 09 Mar 2017