Exploiting Label Skews in Federated Learning with Model Concatenation

11 December 2023

Papers citing "Exploiting Label Skews in Federated Learning with Model Concatenation"

7 / 7 papers shown

Title
Exploiting Label Skewness for Spiking Neural Networks in Federated Learning Di Yu Xin Du Linshan Jiang Shunwen Bai Wentao Tong Shuiguang Deng FedML 26 0 0 23 Dec 2024
Non-IID data in Federated Learning: A Survey with Taxonomy, Metrics, Methods, Frameworks and Future Directions Daniel Gutiérrez David Solans Mikko A. Heikkilä A. Vitaletti Nicolas Kourtellis Aris Anagnostopoulos I. Chatzigiannakis OOD 84 0 0 19 Nov 2024
The Key of Parameter Skew in Federated Learning Sifan Wang Junfeng Liao Ye Yuan Riquan Zhang FedML 24 0 0 21 Aug 2024
Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks Yun-Wei Chu Dong-Jun Han Seyyedali Hosseinalipour Christopher G. Brinton AI4CE FedML 20 1 0 03 Feb 2024
FedLPA: One-shot Federated Learning with Layer-Wise Posterior Aggregation Xiang Liu Liangxi Liu Feiyang Ye Yunheng Shen Xia Li Linshan Jiang Jialin Li 23 4 0 30 Sep 2023
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
Federated Bayesian Optimization via Thompson Sampling Zhongxiang Dai K. H. Low Patrick Jaillet FedML 79 108 0 20 Oct 2020