No One Left Behind: Inclusive Federated Learning over Heterogeneous
Devices

No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices

16 February 2022

Ruixuan Liu

Xing Xie

Papers citing "No One Left Behind: Inclusive Federated Learning over Heterogeneous Devices"

10 / 10 papers shown

Title
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 55 0 0 13 Mar 2025
Heterogeneity-aware Personalized Federated Learning via Adaptive Dual-Agent Reinforcement Learning Xi Chen Qin Li Haibin Cai Ting Wang 60 0 0 28 Jan 2025
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu Cheng Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 99 85 0 27 Jun 2023
When Federated Learning Meets Pre-trained Language Models' Parameter-Efficient Tuning Methods Zhuo Zhang Yuanhang Yang Yong Dai Lizhen Qu Zenglin Xu FedML 46 65 0 20 Dec 2022
A Snapshot of the Frontiers of Client Selection in Federated Learning Gergely Németh M. Lozano Novi Quadrianto Nuria Oliver FedML 102 14 0 27 Sep 2022
Asynchronous Federated Learning on Heterogeneous Devices: A Survey Chenhao Xu Youyang Qu Yong Xiang Longxiang Gao FedML 104 241 0 09 Sep 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
FedNER: Privacy-preserving Medical Named Entity Recognition with Federated Learning Suyu Ge Fangzhao Wu Chuhan Wu Tao Qi Yongfeng Huang Xing Xie 158 56 0 20 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 323 4,212 0 23 Aug 2019
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 297 6,959 0 20 Apr 2018