FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning

22 November 2023

Papers citing "FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning"

5 / 5 papers shown

Title
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead Won-Jun Jang Hyeon-Seo Park Si-Hyeon Lee FedML 178 0 0 10 Feb 2025
FedDr+: Stabilizing Dot-regression with Global Feature Distillation for Federated Learning Seongyoon Kim Minchan Jeong Sungnyun Kim Sungwoo Cho Sumyeong Ahn Se-Young Yun FedML 47 0 0 04 Jun 2024
Towards Understanding and Mitigating Dimensional Collapse in Heterogeneous Federated Learning Yujun Shi Jian Liang Wenqing Zhang Vincent Y. F. Tan Song Bai FedML 79 55 0 01 Oct 2022
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 156 459 0 01 May 2021
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017