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A unified framework for dataset shift diagnostics

17 May 2022

Papers citing "A unified framework for dataset shift diagnostics"

27 / 27 papers shown

Title
A Learning Based Hypothesis Test for Harmful Covariate Shift T. Ginsberg Zhongyuan Liang Rahul G. Krishnan 73 14 0 06 Dec 2022
Online Distribution Shift Detection via Recency Prediction Rachel Luo Rohan Sinha Yixiao Sun Ali Hindy Shengjia Zhao Silvio Savarese Edward Schmerling Marco Pavone 80 10 0 17 Nov 2022
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings Jessica Schrouff Natalie Harris Oluwasanmi Koyejo Ibrahim Alabdulmohsin Eva Schnider ... Vivek Natarajan Alan Karthikesalingam Katherine A. Heller Silvia Chiappa Alexander DÁmour OOD 142 56 0 02 Feb 2022
Local permutation tests for conditional independence Ilmun Kim Matey Neykov Sivaraman Balakrishnan Larry A. Wasserman 74 28 0 22 Dec 2021
Tracking the risk of a deployed model and detecting harmful distribution shifts Aleksandr Podkopaev Aaditya Ramdas 93 27 0 12 Oct 2021
Failing Conceptually: Concept-Based Explanations of Dataset Shift Maleakhi A. Wijaya Dmitry Kazhdan B. Dimanov M. Jamnik 31 7 0 18 Apr 2021
EfficientNetV2: Smaller Models and Faster Training Mingxing Tan Quoc V. Le EgoV 130 2,723 0 01 Apr 2021
Testing for concept shift online V. Vovk 45 22 0 28 Dec 2020
Concept Drift and Covariate Shift Detection Ensemble with Lagged Labels Yiming Xu Diego Klabjan 32 7 0 08 Dec 2020
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift Adaptation Felipe Maia Polo R. Vicente 35 18 0 02 Oct 2020
Telescoping Density-Ratio Estimation Benjamin Rhodes Kai Xu Michael U. Gutmann 153 97 0 22 Jun 2020
Predicting Legal Proceedings Status: Approaches Based on Sequential Text Data Felipe Maia Polo Itamar Ciochetti Emerson Bertolo AILaw 94 3 0 13 Mar 2020
Unsupervised Cross-lingual Representation Learning at Scale Alexis Conneau Kartikay Khandelwal Naman Goyal Vishrav Chaudhary Guillaume Wenzek Francisco Guzmán Edouard Grave Myle Ott Luke Zettlemoyer Veselin Stoyanov 228 6,593 0 05 Nov 2019
Conditional Independence Testing using Generative Adversarial Networks Alexis Bellot M. Schaar CML GAN 78 51 0 09 Jul 2019
Dataset shift quantification for credit card fraud detection Y. Lucas Pierre-Edouard Portier Léa Laporte Sylvie Calabretto Liyun He-Guelton Frédéric Oblé Michael Granitzer 42 24 0 17 Jun 2019
DenseNet Models for Tiny ImageNet Classification Zoheb Abai Nishad Rajmalwar 30 30 0 23 Apr 2019
Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift Stephan Rabanser Stephan Günnemann Zachary Chase Lipton 68 371 0 29 Oct 2018
Quantification under prior probability shift: the ratio estimator and its extensions A. Vaz Rafael Izbicki R. Stern 38 22 0 11 Jul 2018
The Hardness of Conditional Independence Testing and the Generalised Covariance Measure Rajen Dinesh Shah J. Peters 170 303 0 19 Apr 2018
Detecting and Correcting for Label Shift with Black Box Predictors Zachary Chase Lipton Yu Wang Alex Smola OOD 79 558 0 12 Feb 2018
Concept Drift Detection and Adaptation with Hierarchical Hypothesis Testing Shujian Yu Zubin Abraham Heng Wang Mohak Shah Yantao Wei José C. Príncipe 42 53 0 25 Jul 2017
Converting High-Dimensional Regression to High-Dimensional Conditional Density Estimation Rafael Izbicki Ann B. Lee 173 78 0 26 Apr 2017
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 189 406 0 20 Oct 2016
Amortised MAP Inference for Image Super-resolution C. Sønderby Jose Caballero Lucas Theis Wenzhe Shi Ferenc Huszár 99 435 0 14 Oct 2016
Characterizing Concept Drift Geoffrey I. Webb Roy Hyde Hong Cao Hai-Long Nguyen F. Petitjean 48 424 0 12 Nov 2015
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers Kyle Cranmer J. Pavez Gilles Louppe 140 227 0 06 Jun 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,529 0 04 Sep 2014