Omnipredictors for Constrained Optimization

15 September 2022

Papers citing "Omnipredictors for Constrained Optimization"

23 / 23 papers shown

Title
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes Lunjia Hu Charlotte Peale 43 6 0 16 Nov 2022
Loss Minimization through the Lens of Outcome Indistinguishability Parikshit Gopalan Lunjia Hu Michael P. Kim Omer Reingold Udi Wieder UQCV 52 34 0 16 Oct 2022
Making Decisions under Outcome Performativity Michael P. Kim Juan C. Perdomo 60 20 0 04 Oct 2022
Multicalibrated Regression for Downstream Fairness Ira Globus-Harris Varun Gupta Christopher Jung Michael Kearns Jamie Morgenstern Aaron Roth FaML 92 11 0 15 Sep 2022
Individually Fair Learning with One-Sided Feedback Yahav Bechavod Aaron Roth FaML 38 3 0 09 Jun 2022
Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability Lunjia Hu Charlotte Peale Omer Reingold 43 5 0 09 Mar 2022
Omnipredictors Parikshit Gopalan Adam Tauman Kalai Omer Reingold Vatsal Sharan Udi Wieder 69 51 0 11 Sep 2021
Multi-group Agnostic PAC Learnability G. Rothblum G. Yona FaML 110 38 0 20 May 2021
Outcome Indistinguishability Cynthia Dwork Michael P. Kim Omer Reingold G. Rothblum G. Yona 63 62 0 26 Nov 2020
A short note on learning discrete distributions C. Canonne 26 67 0 25 Feb 2020
Average Individual Fairness: Algorithms, Generalization and Experiments Michael Kearns Aaron Roth Saeed Sharifi-Malvajerdi FaML FedML 103 86 0 25 May 2019
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals Andrew Cotter Heinrich Jiang S. Wang Taman Narayan Maya R. Gupta Seungil You Karthik Sridharan 74 155 0 11 Sep 2018
Learning Optimal Fair Policies Razieh Nabi Daniel Malinsky I. Shpitser FaML 39 87 0 06 Sep 2018
Classification with Fairness Constraints: A Meta-Algorithm with Provable Guarantees L. E. Celis Lingxiao Huang Vijay Keswani Nisheeth K. Vishnoi FaML 205 308 0 15 Jun 2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 241 340 0 31 May 2018
Probably Approximately Metric-Fair Learning G. Rothblum G. Yona FaML FedML 45 85 0 08 Mar 2018
Fairness Through Computationally-Bounded Awareness Michael P. Kim Omer Reingold G. Rothblum FaML 85 145 0 08 Mar 2018
A Reductions Approach to Fair Classification Alekh Agarwal A. Beygelzimer Miroslav Dudík John Langford Hanna M. Wallach FaML 224 1,100 0 06 Mar 2018
Empirical Risk Minimization under Fairness Constraints Michele Donini L. Oneto Shai Ben-David John Shawe-Taylor Massimiliano Pontil FaML 76 444 0 23 Feb 2018
Fairness Beyond Disparate Treatment & Disparate Impact: Learning Classification without Disparate Mistreatment Muhammad Bilal Zafar Isabel Valera Manuel Gomez Rodriguez Krishna P. Gummadi FaML 193 1,205 0 26 Oct 2016
Equality of Opportunity in Supervised Learning Moritz Hardt Eric Price Nathan Srebro FaML 222 4,307 0 07 Oct 2016
Satisfying Real-world Goals with Dataset Constraints Gabriel Goh Andrew Cotter Maya R. Gupta M. Friedlander OffRL 60 215 0 24 Jun 2016
Distribution-Specific Agnostic Boosting Vitaly Feldman FedML 92 49 0 16 Sep 2009