One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning

4 March 2021

Papers citing "One for One, or All for All: Equilibria and Optimality of Collaboration in Federated Learning"

5 / 5 papers shown

Title
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? Marco Bornstein Amrit Singh Bedi Abdirisak Mohamed Furong Huang FedML 70 0 0 22 May 2024
Collaborative Machine Learning with Incentive-Aware Model Rewards Rachael Hwee Ling Sim Yehong Zhang M. Chan Hsiang Low FedML 149 126 0 24 Oct 2020
Collaborative Fairness in Federated Learning Lingjuan Lyu Xinyi Xu Qian Wang FedML 68 192 0 27 Aug 2020
Hierarchically Fair Federated Learning Jingfeng Zhang Cheng Li A. Robles-Kelly Mohan Kankanhalli FedML 39 56 0 22 Apr 2020
Free-riders in Federated Learning: Attacks and Defenses Jierui Lin Min Du Jian-Dong Liu FedML 53 113 0 28 Nov 2019