On the Richness of Calibration

8 February 2023

Papers citing "On the Richness of Calibration"

18 / 18 papers shown

Title
Does calibration mean what they say it means; or, the reference class problem rises again Lily Hu FaML 108 0 0 21 Dec 2024
Variable-Based Calibration for Machine Learning Classifiers Mark Kelly Padhraic Smyth 39 4 0 30 Sep 2022
Risk Measures and Upper Probabilities: Coherence and Stratification Christiane Fröhlich Robert C. Williamson 30 14 0 07 Jun 2022
Towards Intersectionality in Machine Learning: Including More Identities, Handling Underrepresentation, and Performing Evaluation Angelina Wang V. V. Ramaswamy Olga Russakovsky FaML 50 94 0 10 May 2022
Low-Degree Multicalibration Parikshit Gopalan Michael P. Kim M. Singhal Shengjia Zhao FaML UQCV 46 41 0 02 Mar 2022
Scaffolding Sets M. Burhanpurkar Zhun Deng Cynthia Dwork Linjun Zhang 53 9 0 04 Nov 2021
Escaping the Impossibility of Fairness: From Formal to Substantive Algorithmic Fairness Ben Green FaML 88 38 0 09 Jul 2021
Local Calibration: Metrics and Recalibration Rachel Luo Aadyot Bhatnagar Yu Bai Shengjia Zhao Huan Wang Caiming Xiong Silvio Savarese Stefano Ermon Edward Schmerling Marco Pavone 39 14 0 22 Feb 2021
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 71 488 0 02 Apr 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 151 198 0 19 Feb 2019
Fairness risk measures Robert C. Williamson A. Menon FaML 138 140 0 24 Jan 2019
A Unified Approach to Quantifying Algorithmic Unfairness: Measuring Individual & Group Unfairness via Inequality Indices Till Speicher Hoda Heidari Nina Grgic-Hlaca Krishna P. Gummadi Adish Singla Adrian Weller Muhammad Bilal Zafar FaML 58 263 0 02 Jul 2018
Multiaccuracy: Black-Box Post-Processing for Fairness in Classification Michael P. Kim Amirata Ghorbani James Zou MLAU 241 339 0 31 May 2018
Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness Michael Kearns Seth Neel Aaron Roth Zhiwei Steven Wu FaML 185 776 0 14 Nov 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 291 5,825 0 14 Jun 2017
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 297 2,109 0 24 Oct 2016
Inherent Trade-Offs in the Fair Determination of Risk Scores Jon M. Kleinberg S. Mullainathan Manish Raghavan FaML 114 1,768 0 19 Sep 2016
On Individual Risk P. Dawid 59 17 0 20 Jun 2014