Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning

22 August 2023

Papers citing "Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning"

8 / 8 papers shown

Title
LiteChain: A Lightweight Blockchain for Verifiable and Scalable Federated Learning in Massive Edge Networks Handi Chen Rui Zhou Yun-Hin Chan Zhihan Jiang Xianhao Chen Edith C. H. Ngai 47 0 0 06 Mar 2025
Federated Learning with Sample-level Client Drift Mitigation Haoran Xu Jiaze Li Wanyi Wu Hao Ren FedML 41 0 0 20 Jan 2025
Selective Aggregation for Low-Rank Adaptation in Federated Learning Pengxin Guo Shuang Zeng Y. Wang Huijie Fan Feifei Wang Liangqiong Qu FedML 36 8 0 02 Oct 2024
Exploiting Features and Logits in Heterogeneous Federated Learning Yun-Hin Chan Edith C. H. Ngai FedML 19 2 0 27 Oct 2022
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks Hankyul Baek Won Joon Yun Yunseok Kwak Soyi Jung Mingyue Ji M. Bennis Jihong Park Joongheon Kim FedML 62 20 0 05 Dec 2021
FedProto: Federated Prototype Learning across Heterogeneous Clients Yue Tan Guodong Long Lu Liu Tianyi Zhou Qinghua Lu Jing Jiang Chengqi Zhang FedML 151 455 0 01 May 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 176 267 0 26 Feb 2021
Federated Learning on Non-IID Data Silos: An Experimental Study Q. Li Yiqun Diao Quan Chen Bingsheng He FedML OOD 85 943 0 03 Feb 2021