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covariate shift

199 papers

Papers

A One-step Approach to Covariate Shift Adaptation ACML 2020 Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation AISTATS 2020 Disagreement-Regularized Imitation Learning ICLR 2020 Distributionally Robust Policy Evaluation and Learning in Offline Contextual Bandits ICML 2020 Ensembles of Locally Independent Prediction Models AAAI 2020 Identifying Causal-Effect Inference Failure with Uncertainty-Aware Models NeurIPS 2020 Improving robustness against common corruptions by covariate shift adaptation NeurIPS 2020 Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling ICLR 2020 Mix and Match: An Optimistic Tree-Search Approach for Learning Models from Mixture Distributions NeurIPS 2020 Off-Policy Evaluation and Learning for External Validity under a Covariate Shift NeurIPS 2020 Robust causal inference under covariate shift via worst-case subpopulation treatment effects COLT 2020 Robust Correction of Sampling Bias using Cumulative Distribution Functions NeurIPS 2020 Robust Learning with the Hilbert-Schmidt Independence Criterion ICML 2020 Robustness to Spurious Correlations via Human Annotations ICML 2020 Simulator Calibration under Covariate Shift with Kernels AISTATS 2020 Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift ICML 2020 Weakly-Supervised Disentanglement Without Compromises ICML 2020 A Generalized Neyman-Pearson Criterion for Optimal Domain Adaptation ALT 2019 Bias Reduction via End-to-End Shift Learning: Application to Citizen Science AAAI 2019 Conformal Prediction Under Covariate Shift NeurIPS 2019 Covariate Shift Adaptation on Learning from Positive and Unlabeled Data AAAI 2019 Differentially Private Distributed Data Summarization under Covariate Shift NeurIPS 2019 Failing Loudly: An Empirical Study of Methods for Detecting Dataset Shift NeurIPS 2019 Low-Dimensional Density Ratio Estimation for Covariate Shift Correction AISTATS 2019 Off-Policy Deep Reinforcement Learning by Bootstrapping the Covariate Shift AAAI 2019