Outcome Indistinguishability

26 November 2020

Papers citing "Outcome Indistinguishability"

47 / 47 papers shown

Title
How Global Calibration Strengthens Multiaccuracy Sílvia Casacuberta Parikshit Gopalan Varun Kanade Omer Reingold 32 0 0 21 Apr 2025
Revisiting the Predictability of Performative, Social Events Juan C. Perdomo 46 1 0 12 Mar 2025
Conformal Prediction and Human Decision Making Jessica Hullman Yifan Wu Dawei Xie Ziyang Guo Andrew Gelman 42 0 0 12 Mar 2025
When does a predictor know its own loss? Aravind Gollakota Parikshit Gopalan Aayush Karan Charlotte Peale Udi Wieder UQCV FaML 67 0 0 27 Feb 2025
Learning With Multi-Group Guarantees For Clusterable Subpopulations Jessica Dai Nika Haghtalab Eric Zhao 31 0 0 18 Oct 2024
When is Multicalibration Post-Processing Necessary? Dutch Hansen Siddartha Devic Preetum Nakkiran Vatsal Sharan 43 4 0 10 Jun 2024
Reconciling Model Multiplicity for Downstream Decision Making Ally Yalei Du Dung Daniel Ngo Zhiwei Steven Wu 37 5 0 30 May 2024
Fair Risk Control: A Generalized Framework for Calibrating Multi-group Fairness Risks Lujing Zhang Aaron Roth Linjun Zhang FaML 19 6 0 03 May 2024
Cryptographic Hardness of Score Estimation Min Jae Song 33 0 0 04 Apr 2024
Testing Calibration in Nearly-Linear Time Lunjia Hu A. Jambulapati Kevin Tian Chutong Yang 35 0 0 20 Feb 2024
On Computationally Efficient Multi-Class Calibration Parikshit Gopalan Lunjia Hu G. Rothblum 14 6 0 12 Feb 2024
Human Expertise in Algorithmic Prediction Rohan Alur Manish Raghavan Devavrat Shah 17 1 0 01 Feb 2024
Multi-group Learning for Hierarchical Groups Samuel Deng Daniel Hsu AI4CE 39 1 0 01 Feb 2024
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics Charles Marx Sofian Zalouk Stefano Ermon 27 6 0 31 Oct 2023
Performative Prediction: Past and Future Moritz Hardt Celestine Mendler-Dünner 31 21 0 25 Oct 2023
On the Vulnerability of Fairness Constrained Learning to Malicious Noise Avrim Blum Princewill Okoroafor Aadirupa Saha Kevin Stangl 29 1 0 21 Jul 2023
Loss Minimization Yields Multicalibration for Large Neural Networks Jarosław Błasiok Parikshit Gopalan Lunjia Hu Adam Tauman Kalai Preetum Nakkiran FaML UQCV 46 10 0 19 Apr 2023
HappyMap: A Generalized Multi-calibration Method Zhun Deng Cynthia Dwork Linjun Zhang 68 17 0 08 Mar 2023
Group conditional validity via multi-group learning Samuel Deng Navid Ardeshir Daniel J. Hsu 35 1 0 07 Mar 2023
Generative Models of Huge Objects Lunjia Hu Inbal Livni-Navon Omer Reingold 34 1 0 24 Feb 2023
A Unifying Perspective on Multi-Calibration: Game Dynamics for Multi-Objective Learning Nika Haghtalab Michael I. Jordan Eric Zhao 35 8 0 21 Feb 2023
The Scope of Multicalibration: Characterizing Multicalibration via Property Elicitation Georgy Noarov Aaron Roth 35 4 0 16 Feb 2023
Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration Parikshit Gopalan Michael P. Kim Omer Reingold 22 15 0 13 Feb 2023
From Pseudorandomness to Multi-Group Fairness and Back Cynthia Dwork Daniel Lee Huijia Lin Pranay Tankala FaML 24 9 0 21 Jan 2023
A Unifying Theory of Distance from Calibration Jarosław Błasiok Parikshit Gopalan Lunjia Hu Preetum Nakkiran 31 32 0 30 Nov 2022
Comparative Learning: A Sample Complexity Theory for Two Hypothesis Classes Lunjia Hu Charlotte Peale 43 6 0 16 Nov 2022
On-Demand Sampling: Learning Optimally from Multiple Distributions Nika Haghtalab Michael I. Jordan Eric Zhao FedML 50 34 0 22 Oct 2022
Loss Minimization through the Lens of Outcome Indistinguishability Parikshit Gopalan Lunjia Hu Michael P. Kim Omer Reingold Udi Wieder UQCV 35 31 0 16 Oct 2022
Making Decisions under Outcome Performativity Michael P. Kim Juan C. Perdomo 46 20 0 04 Oct 2022
Omnipredictors for Constrained Optimization Lunjia Hu Inbal Livni-Navon Omer Reingold Chutong Yang 23 14 0 15 Sep 2022
Multicalibrated Regression for Downstream Fairness Ira Globus-Harris Varun Gupta Christopher Jung Michael Kearns Jamie Morgenstern Aaron Roth FaML 52 11 0 15 Sep 2022
Reconciling Individual Probability Forecasts Aaron Roth A. Tolbert S. Weinstein 27 14 0 04 Sep 2022
Is your model predicting the past? Moritz Hardt Michael P. Kim 18 11 0 23 Jun 2022
Adversarial Scrutiny of Evidentiary Statistical Software Rediet Abebe Moritz Hardt Angela Jin John Miller Ludwig Schmidt Rebecca Wexler 33 5 0 19 Jun 2022
Fair Algorithm Design: Fair and Efficacious Machine Scheduling April Niu Agnes Totschnig A. Vetta FaML 23 3 0 13 Apr 2022
Decision-Making under Miscalibration G. Rothblum G. Yona 16 5 0 18 Mar 2022
Metric Entropy Duality and the Sample Complexity of Outcome Indistinguishability Lunjia Hu Charlotte Peale Omer Reingold 21 5 0 09 Mar 2022
Low-Degree Multicalibration Parikshit Gopalan Michael P. Kim M. Singhal Shengjia Zhao FaML UQCV 22 37 0 02 Mar 2022
An Exploration of Multicalibration Uniform Convergence Bounds Harrison Rosenberg Robi Bhattacharjee Kassem Fawaz S. Jha 22 1 0 09 Feb 2022
An Algorithmic Framework for Bias Bounties Ira Globus-Harris Michael Kearns Aaron Roth FedML 102 24 0 25 Jan 2022
Minimax Optimality (Probably) Doesn't Imply Distribution Learning for GANs Sitan Chen Jungshian Li Yuanzhi Li Raghu Meka GAN 11 4 0 18 Jan 2022
Simple and near-optimal algorithms for hidden stratification and multi-group learning Abdoreza Asadpour Daniel J. Hsu 105 20 0 22 Dec 2021
Scaffolding Sets M. Burhanpurkar Zhun Deng Cynthia Dwork Linjun Zhang 35 9 0 04 Nov 2021
Omnipredictors Parikshit Gopalan Adam Tauman Kalai Omer Reingold Vatsal Sharan Udi Wieder 16 47 0 11 Sep 2021
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration Shengjia Zhao Michael P. Kim Roshni Sahoo Tengyu Ma Stefano Ermon 20 55 0 12 Jul 2021
Multicalibrated Partitions for Importance Weights Parikshit Gopalan Omer Reingold Vatsal Sharan Udi Wieder 13 11 0 10 Mar 2021
Online Multivalid Learning: Means, Moments, and Prediction Intervals Varun Gupta Christopher Jung Georgy Noarov Mallesh M. Pai Aaron Roth 27 40 0 05 Jan 2021