FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes

FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes

22 February 2025

Papers citing "FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes"

11 / 11 papers shown

Title
FedTGP: Trainable Global Prototypes with Adaptive-Margin-Enhanced Contrastive Learning for Data and Model Heterogeneity in Federated Learning Jianqing Zhang Yang Liu Yang Hua Jian Cao FedML 83 44 0 06 Jan 2024
FedGH: Heterogeneous Federated Learning with Generalized Global Header Liping Yi Gang Wang Xiaoguang Liu Zhuan Shi Han Yu FedML 68 75 0 23 Mar 2023
Constrained Few-shot Class-incremental Learning Michael Hersche G. Karunaratne G. Cherubini Luca Benini Abu Sebastian Abbas Rahimi CLL 72 142 0 30 Mar 2022
Federated Dropout -- A Simple Approach for Enabling Federated Learning on Resource Constrained Devices Dingzhu Wen Ki-Jun Jeon Kaibin Huang FedML 85 90 0 30 Sep 2021
FedKD: Communication Efficient Federated Learning via Knowledge Distillation Chuhan Wu Fangzhao Wu Lingjuan Lyu Yongfeng Huang Xing Xie FedML 46 383 0 30 Aug 2021
No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data Mi Luo Fei Chen Dapeng Hu Yifan Zhang Jian Liang Jiashi Feng FedML 58 332 0 09 Jun 2021
Data-Free Knowledge Distillation for Heterogeneous Federated Learning Zhuangdi Zhu Junyuan Hong Jiayu Zhou FedML 43 645 0 20 May 2021
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients Enmao Diao Jie Ding Vahid Tarokh FedML 65 550 0 03 Oct 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 70 554 0 06 Jan 2020
FedMD: Heterogenous Federated Learning via Model Distillation Daliang Li Junpu Wang FedML 67 845 0 08 Oct 2019
OLÉ: Orthogonal Low-rank Embedding, A Plug and Play Geometric Loss for Deep Learning José Lezama Qiang Qiu Pablo Musé Guillermo Sapiro 44 78 0 05 Dec 2017