FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality

2 April 2024

Papers citing "FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality"

9 / 9 papers shown

Title
HappyMap: A Generalized Multi-calibration Method Zhun Deng Cynthia Dwork Linjun Zhang 181 19 0 08 Mar 2023
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information Pranjal Awasthi Alex Beutel Matthaeus Kleindessner Jamie Morgenstern Xuezhi Wang FaML 58 57 0 16 Feb 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 250 128 0 04 Jan 2021
Minimax Pareto Fairness: A Multi Objective Perspective Natalia Martínez Martín Bertrán Guillermo Sapiro FaML 61 191 0 03 Nov 2020
Transfer Learning for High-dimensional Linear Regression: Prediction, Estimation, and Minimax Optimality Sai Li T. Tony Cai Hongzhe Li 85 162 0 18 Jun 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 198 2,044 0 16 Apr 2020
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 85 1,236 0 20 Nov 2019
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 99 1,767 0 19 Sep 2016
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 114 966 0 06 Jan 2015