Minimax Pareto Fairness: A Multi Objective Perspective

3 November 2020

Papers citing "Minimax Pareto Fairness: A Multi Objective Perspective"

20 / 120 papers shown

Title
Multiaccurate Proxies for Downstream Fairness Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth Saeed Sharifi-Malvajerdi 35 21 0 09 Jul 2021
The Spotlight: A General Method for Discovering Systematic Errors in Deep Learning Models G. dÉon Jason dÉon J. R. Wright Kevin Leyton-Brown 33 74 0 01 Jul 2021
A Unified Approach to Fair Online Learning via Blackwell Approachability Evgenii Chzhen Christophe Giraud Gilles Stoltz FaML 14 11 0 23 Jun 2021
Fair Normalizing Flows Mislav Balunović Anian Ruoss Martin Vechev AAML 19 36 0 10 Jun 2021
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning Yuyan Wang Xuezhi Wang Alex Beutel Flavien Prost Jilin Chen Ed H. Chi FaML 27 47 0 04 Jun 2021
Multi-fairness under class-imbalance Arjun Roy Vasileios Iosifidis Eirini Ntoutsi FaML 11 6 0 27 Apr 2021
Pareto Efficient Fairness in Supervised Learning: From Extraction to Tracing Mohammad Mahdi Kamani R. Forsati Jianmin Wang M. Mahdavi FaML 13 11 0 04 Apr 2021
Adaptive Sampling for Minimax Fair Classification S. Shekhar Greg Fields Mohammad Ghavamzadeh T. Javidi FaML 45 37 0 01 Mar 2021
Towards Unbiased and Accurate Deferral to Multiple Experts Vijay Keswani Matthew Lease K. Kenthapadi FaML 8 67 0 25 Feb 2021
Lexicographically Fair Learning: Algorithms and Generalization Emily Diana Wesley Gill Ira Globus-Harris Michael Kearns Aaron Roth Saeed Sharifi-Malvajerdi FedML FaML 65 9 0 16 Feb 2021
Technical Challenges for Training Fair Neural Networks Valeriia Cherepanova V. Nanda Micah Goldblum John P. Dickerson Tom Goldstein FaML 25 22 0 12 Feb 2021
MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset Chuizheng Meng Loc Trinh Nan Xu Yan Liu 24 30 0 12 Feb 2021
A Hybrid 2-stage Neural Optimization for Pareto Front Extraction Gurpreet Singh Soumyajit Gupta Matthew Lease Clint Dawson 23 3 0 27 Jan 2021
No Subclass Left Behind: Fine-Grained Robustness in Coarse-Grained Classification Problems N. Sohoni Jared A. Dunnmon Geoffrey Angus Albert Gu Christopher Ré 30 242 0 25 Nov 2020
Statistical Inference for Maximin Effects: Identifying Stable Associations across Multiple Studies Zijian Guo 28 17 0 15 Nov 2020
Minimax Group Fairness: Algorithms and Experiments Emily Diana Wesley Gill Michael Kearns K. Kenthapadi Aaron Roth FaML FedML 6 22 0 05 Nov 2020
Learning the Pareto Front with Hypernetworks Aviv Navon Aviv Shamsian Gal Chechik Ethan Fetaya 28 139 0 08 Oct 2020
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation Kate Donahue Jon M. Kleinberg FedML 24 79 0 02 Oct 2020
Algorithms and Learning for Fair Portfolio Design Emily Diana Travis Dick Hadi Elzayn Michael Kearns Aaron Roth Zachary Schutzman Saeed Sharifi-Malvajerdi Juba Ziani FaML 8 6 0 12 Jun 2020
Active Sampling for Min-Max Fairness Jacob D. Abernethy Pranjal Awasthi Matthäus Kleindessner Jamie Morgenstern Chris Russell Jie Zhang FaML 19 49 0 11 Jun 2020