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Distribution Shift

196 papers

Papers per year

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Papers

The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers NIPS 2019
Distributionally Robust Semi-Supervised Learning for People-Centric Sensing AAAI 2019
On Target Shift in Adversarial Domain Adaptation AISTATS 2019
Unsupervised Domain Adaptation Using Feature-Whitening and Consensus Loss CVPR 2019
To Annotate or Not? Predicting Performance Drop under Domain Shift EMNLP 2019
Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction EMNLP 2019
Distributionally Robust Graphical Models NIPS 2018
Beyond Worst-case: A Probabilistic Analysis of Affine Policies in Dynamic Optimization NIPS 2017
Robust Optimization for Non-Convex Objectives NIPS 2017
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching NIPS 2017
Stochastic Gradient Methods for Distributionally Robust Optimization with f-divergences NIPS 2016
Learning With Dataset Bias in Latent Subcategory Models CVPR 2015
Robust Classification Under Sample Selection Bias NIPS 2014
Data-driven Distributionally Robust Polynomial Optimization NIPS 2013
Learning High-Density Regions for a Generalized Kolmogorov-Smirnov Test in High-Dimensional Data NIPS 2012
Active Learning with a Drifting Distribution NIPS 2011
Relative Density-Ratio Estimation for Robust Distribution Comparison NIPS 2011
Learning Bounds for Importance Weighting NIPS 2010
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation NIPS 2007
Correcting Sample Selection Bias by Unlabeled Data NIPS 2006
Mixture Regression for Covariate Shift NIPS 2006