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Calibrated Learning to Defer with One-vs-All Classifiers

8 February 2022

Papers citing "Calibrated Learning to Defer with One-vs-All Classifiers"

27 / 27 papers shown

Title
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 135 4 0 29 May 2024
Learning To Guide Human Decision Makers With Vision-Language Models Debodeep Banerjee Stefano Teso Burcu Sayin Andrea Passerini 77 1 0 25 Mar 2024
Top-label calibration and multiclass-to-binary reductions Chirag Gupta Aaditya Ramdas 103 37 0 18 Jul 2021
Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration Shengjia Zhao Michael P. Kim Roshni Sahoo Tengyu Ma Stefano Ermon 67 58 0 12 Jul 2021
MLP-Mixer: An all-MLP Architecture for Vision Ilya O. Tolstikhin N. Houlsby Alexander Kolesnikov Lucas Beyer Xiaohua Zhai ... Andreas Steiner Daniel Keysers Jakob Uszkoreit Mario Lucic Alexey Dosovitskiy 441 2,694 0 04 May 2021
Differentiable Learning Under Triage Nastaran Okati A. De Manuel Gomez Rodriguez 96 64 0 16 Mar 2021
Classification with Rejection Based on Cost-sensitive Classification Nontawat Charoenphakdee Zhenghang Cui Yivan Zhang Masashi Sugiyama 138 67 0 22 Oct 2020
Consistent Estimators for Learning to Defer to an Expert Hussein Mozannar David Sontag 61 205 0 02 Jun 2020
Learning to Complement Humans Bryan Wilder Eric Horvitz Ece Kamar 171 168 0 01 May 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 91 383 0 28 Oct 2019
A Survey of Deep Learning Techniques for Autonomous Driving Sorin Grigorescu Bogdan Trasnea Tiberiu T. Cocias G. Macesanu 3DPC 98 1,402 0 17 Oct 2019
Neural Legal Judgment Prediction in English Ilias Chalkidis Ion Androutsopoulos Nikolaos Aletras AILaw ELM 176 341 0 05 Jun 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 196 3,458 0 28 Mar 2019
The Algorithmic Automation Problem: Prediction, Triage, and Human Effort M. Raghu Katy Blumer G. Corrado Jon M. Kleinberg Ziad Obermeyer S. Mullainathan 156 140 0 28 Mar 2019
Evaluating model calibration in classification Juozas Vaicenavicius David Widmann Carl R. Andersson Fredrik Lindsten Jacob Roll Thomas B. Schon UQCV 157 200 0 19 Feb 2019
On the Calibration of Multiclass Classification with Rejection Chenri Ni Nontawat Charoenphakdee Junya Honda Masashi Sugiyama 55 55 0 30 Jan 2019
To Trust Or Not To Trust A Classifier Heinrich Jiang Been Kim Melody Y. Guan Maya R. Gupta UQCV 179 473 0 30 May 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer David Madras T. Pitassi R. Zemel FaML 177 221 0 17 Nov 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 299 5,877 0 14 Jun 2017
Automated Hate Speech Detection and the Problem of Offensive Language Thomas Davidson Dana Warmsley M. Macy Ingmar Weber 79 2,703 0 11 Mar 2017
FastText.zip: Compressing text classification models Armand Joulin Edouard Grave Piotr Bojanowski Matthijs Douze Hervé Jégou Tomas Mikolov MQ 96 1,216 0 12 Dec 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 362 8,005 0 23 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 2.1K 150,433 0 22 Dec 2014
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images Anh Totti Nguyen J. Yosinski Jeff Clune AAML 174 3,275 0 05 Dec 2014
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 646 13,438 0 25 Aug 2014
Composite Binary Losses Mark D. Reid Robert C. Williamson 160 223 0 17 Dec 2009