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T-Cal: An optimal test for the calibration of predictive models

3 March 2022

Papers citing "T-Cal: An optimal test for the calibration of predictive models"

34 / 34 papers shown

Title
Reassessing How to Compare and Improve the Calibration of Machine Learning Models M. Chidambaram Rong Ge 107 2 0 06 Jun 2024
Metrics of calibration for probabilistic predictions Imanol Arrieta-Ibarra Paman Gujral Jonathan Tannen M. Tygert Cherie Xu 80 22 0 19 May 2022
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control Anastasios Nikolas Angelopoulos Stephen Bates Emmanuel J. Candès Michael I. Jordan Lihua Lei 271 134 0 03 Oct 2021
Goodness-of-fit testing for Hölder continuous densities under local differential privacy A. Dubois Thomas B. Berrett C. Butucea 40 4 0 06 Jul 2021
Exact Distribution-Free Hypothesis Tests for the Regression Function of Binary Classification via Conditional Kernel Mean Embeddings Ambrus Tamás Balázs Csanád Csáji 52 4 0 08 Mar 2021
Don't Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification Yu Bai Song Mei Haiquan Wang Caiming Xiong 53 42 0 15 Feb 2021
Mitigating Bias in Calibration Error Estimation Rebecca Roelofs Nicholas Cain Jonathon Shlens Michael C. Mozer 75 95 0 15 Dec 2020
Distribution-free binary classification: prediction sets, confidence intervals and calibration Chirag Gupta Aleksandr Podkopaev Aaditya Ramdas UQCV 89 82 0 18 Jun 2020
Individual Calibration with Randomized Forecasting Shengjia Zhao Tengyu Ma Stefano Ermon 70 60 0 18 Jun 2020
Towards optimal doubly robust estimation of heterogeneous causal effects Edward H. Kennedy CML 168 326 0 29 Apr 2020
Minimax optimality of permutation tests Ilmun Kim Sivaraman Balakrishnan Larry A. Wasserman 61 48 0 30 Mar 2020
Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning Jize Zhang B. Kailkhura T. Y. Han UQCV 90 227 0 16 Mar 2020
Calibrating Deep Neural Networks using Focal Loss Jishnu Mukhoti Viveka Kulharia Amartya Sanyal Stuart Golodetz Philip Torr P. Dokania UQCV 85 465 0 21 Feb 2020
Optimal rates for independence testing via $U$ -statistic permutation tests Thomas B. Berrett Ioannis Kontoyiannis R. Samworth 48 26 0 15 Jan 2020
Beyond temperature scaling: Obtaining well-calibrated multiclass probabilities with Dirichlet calibration Meelis Kull Miquel Perelló Nieto Markus Kängsepp Telmo de Menezes e Silva Filho Hao Song Peter A. Flach UQCV 78 382 0 28 Oct 2019
Calibration tests in multi-class classification: A unifying framework David Widmann Fredrik Lindsten Dave Zachariah 81 94 0 24 Oct 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 176 357 0 23 Sep 2019
On Mixup Training: Improved Calibration and Predictive Uncertainty for Deep Neural Networks S. Thulasidasan Gopinath Chennupati J. Bilmes Tanmoy Bhattacharya S. Michalak UQCV 68 545 0 27 May 2019
Measuring Calibration in Deep Learning Jeremy Nixon Michael W. Dusenberry Ghassen Jerfel Timothy Nguyen Jeremiah Zhe Liu Linchuan Zhang Dustin Tran UQCV 77 491 0 02 Apr 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 157 199 0 19 Feb 2019
Conformal calibrators V. Vovk Ivan Petej Paolo Toccaceli A. Gammerman 235 26 0 18 Feb 2019
Simulator Calibration under Covariate Shift with Kernels Keiichi Kisamori Motonobu Kanagawa Keisuke Yamazaki 45 11 0 21 Sep 2018
Dirichlet-based Gaussian Processes for Large-scale Calibrated Classification Dimitrios Milios Raffaello Camoriano Pietro Michiardi Lorenzo Rosasco Maurizio Filippone UQCV 69 75 0 28 May 2018
Cross-Fitting and Fast Remainder Rates for Semiparametric Estimation Whitney Newey Jamie Robins 71 147 0 27 Jan 2018
Hypothesis Testing for High-Dimensional Multinomials: A Selective Review Sivaraman Balakrishnan Larry A. Wasserman 76 65 0 17 Dec 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,862 0 14 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Remember the Curse of Dimensionality: The Case of Goodness-of-Fit Testing in Arbitrary Dimension E. Arias-Castro Bruno Pelletier Venkatesh Saligrama 74 35 0 27 Jul 2016
End to End Learning for Self-Driving Cars Mariusz Bojarski D. Testa Daniel Dworakowski Bernhard Firner B. Flepp ... Urs Muller Jiakai Zhang Xin Zhang Jake Zhao Karol Zieba SSL 100 4,175 0 25 Apr 2016
Lepski's Method and Adaptive Estimation of Nonlinear Integral Functionals of Density Rajarshi Mukherjee E. T. Tchetgen J. M. Robins 38 10 0 02 Aug 2015
Higher Criticism for Large-Scale Inference, Especially for Rare and Weak Effects D. Donoho Jiashun Jin 61 131 0 17 Oct 2014
Rare and Weak effects in Large-Scale Inference: methods and phase diagrams Jiashun Jin Tracy Ke 84 49 0 16 Oct 2014
Higher order influence functions and minimax estimation of nonlinear functionals J. M. Robins Lingling Li E. T. Tchetgen A. van der Vaart 309 241 0 20 May 2008
A simple adaptive estimator of the integrated square of a density Evarist Giné Richard Nickl 176 63 0 06 Mar 2008