On the Interconnections of Calibration, Quantification, and Classifier Accuracy Prediction under Dataset Shift

16 May 2025

Papers citing "On the Interconnections of Calibration, Quantification, and Classifier Accuracy Prediction under Dataset Shift"

22 / 22 papers shown

Title
Quantification using Permutation-Invariant Networks based on Histograms Olaya Pérez-Mon Alejandro Moreo Juan José del Coz Pablo González MQ 35 2 0 22 Mar 2024
Kernel Density Estimation for Multiclass Quantification Alejandro Moreo Pablo González Juan José del Coz 32 7 0 31 Dec 2023
Invariance assumptions for class distribution estimation Dirk Tasche OOD 61 4 0 28 Nov 2023
Label Shift Quantification with Robustness Guarantees via Distribution Feature Matching Bastien Dussap Gilles Blanchard Badr-Eddine Chérief-Abdellatif OOD 39 8 0 07 Jun 2023
Leveraging Unlabeled Data to Predict Out-of-Distribution Performance Saurabh Garg Sivaraman Balakrishnan Zachary Chase Lipton Behnam Neyshabur Hanie Sedghi OODD OOD 78 131 0 11 Jan 2022
Soft Calibration Objectives for Neural Networks A. Karandikar Nicholas Cain Dustin Tran Balaji Lakshminarayanan Jonathon Shlens Michael C. Mozer Becca Roelofs UQCV 88 90 0 30 Jul 2021
Predicting with Confidence on Unseen Distributions Devin Guillory Vaishaal Shankar Sayna Ebrahimi Trevor Darrell Ludwig Schmidt UQCV OOD 68 123 0 07 Jul 2021
Mandoline: Model Evaluation under Distribution Shift Mayee F. Chen Karan Goel N. Sohoni Fait Poms Kayvon Fatahalian Christopher Ré 70 72 0 01 Jul 2021
Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles Jiefeng Chen Frederick Liu Besim Avci Xi Wu Yingyu Liang S. Jha 85 64 0 29 Jun 2021
Assessing Generalization of SGD via Disagreement Yiding Jiang Vaishnavh Nagarajan Christina Baek J. Zico Kolter 95 115 0 25 Jun 2021
QuaPy: A Python-Based Framework for Quantification Alejandro Moreo Andrea Esuli Fabrizio Sebastiani 35 21 0 18 Jun 2021
A Comparative Evaluation of Quantification Methods Tobias Schumacher M. Strohmaier Florian Lemmerich MQ 59 14 0 04 Mar 2021
Tweet Sentiment Quantification: An Experimental Re-Evaluation Alejandro Moreo Fabrizio Sebastiani 26 17 0 04 Nov 2020
A Unified View of Label Shift Estimation Saurabh Garg Yifan Wu Sivaraman Balakrishnan Zachary Chase Lipton 72 146 0 17 Mar 2020
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter Victor Sanh Lysandre Debut Julien Chaumond Thomas Wolf 255 7,547 0 02 Oct 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 677 24,541 0 26 Jul 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 185 1,702 0 06 Jun 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 61 370 0 29 Oct 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 95,175 0 11 Oct 2018
Evaluation Measures for Quantification: An Axiomatic Approach Fabrizio Sebastiani 52 35 0 06 Sep 2018
Detecting and Correcting for Label Shift with Black Box Predictors Zachary Chase Lipton Yu Wang Alex Smola OOD 73 558 0 12 Feb 2018
Should we really use post-hoc tests based on mean-ranks? A. Benavoli Giorgio Corani Francesca Mangili 52 380 0 09 May 2015