covariate shift

Understanding Simultaneous Train and Test Robustness ALT 2022 Using Mixup as a Regularizer Can Surprisingly Improve Accuracy & Out-of-Distribution Robustness NeurIPS 2022 Adapting Event Extractors to Medical Data: Bridging the Covariate Shift EACL 2021 Bayesian Adaptation for Covariate Shift NeurIPS 2021 Confidence Calibration for Domain Generalization Under Covariate Shift ICCV 2021 Dangers of Bayesian Model Averaging under Covariate Shift NeurIPS 2021 Designing Transportable Experiments Under S-admissability AISTATS 2021 Domain adaptation under structural causal models JMLR 2021 Efficient Learning with Arbitrary Covariate Shift ALT 2021 Empirical or Invariant Risk Minimization? A Sample Complexity Perspective ICLR 2021 Error-Aware Imitation Learning from Teleoperation Data for Mobile Manipulation CoRL 2021 Examining and Combating Spurious Features under Distribution Shift ICML 2021 Learning from Biased Data: A Semi-Parametric Approach ICML 2021 Measuring Dependence with Matrix-based Entropy Functional AAAI 2021 Metadata Normalization CVPR 2021 Mitigating Covariate Shift in Imitation Learning via Offline Data With Partial Coverage NeurIPS 2021 Near-Optimal Linear Regression under Distribution Shift ICML 2021 Out-of-Distribution Generalization via Risk Extrapolation (REx) ICML 2021 Overparameterization Improves Robustness to Covariate Shift in High Dimensions NeurIPS 2021 Reducing the Covariate Shift by Mirror Samples in Cross Domain Alignment NeurIPS 2021 Robust Fairness Under Covariate Shift AAAI 2021 Self-Tuning Bandits over Unknown Covariate-Shifts ALT 2021 SurvITE: Learning Heterogeneous Treatment Effects from Time-to-Event Data NeurIPS 2021 Weighted model estimation for offline model-based reinforcement learning NeurIPS 2021 We Need To Talk About Random Splits EACL 2021