Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition

21 July 2023

Papers citing "Demystifying Local and Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition"

7 / 7 papers shown

Title
Quantifying Knowledge Distillation Using Partial Information Decomposition Pasan Dissanayake Faisal Hamman Barproda Halder Ilia Sucholutsky Qiuyi Zhang Sanghamitra Dutta 36 0 0 12 Nov 2024
PraFFL: A Preference-Aware Scheme in Fair Federated Learning Rongguang Ye Wei-Bin Kou Ming Tang FedML 31 4 0 13 Apr 2024
Can Information Flows Suggest Targets for Interventions in Neural Circuits? Praveen Venkatesh Sanghamitra Dutta Neil Mehta P. Grover AAML 24 8 0 09 Nov 2021
Enforcing fairness in private federated learning via the modified method of differential multipliers Borja Rodríguez Gálvez Filip Granqvist Rogier van Dalen M. Seigel FedML 36 51 0 17 Sep 2021
FedFair: Training Fair Models In Cross-Silo Federated Learning Lingyang Chu Lanjun Wang Yanjie Dong J. Pei Zirui Zhou Yong Zhang FedML 56 40 0 13 Sep 2021
Estimating the Unique Information of Continuous Variables Ari Pakman Amin Nejatbakhsh D. Gilboa Abdullah Makkeh Luca Mazzucato Michael Wibral E. Schneidman 30 24 0 30 Jan 2021
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 294 4,143 0 23 Aug 2019