Distribution Shift

Adapting to Online Label Shift with Provable Guarantees NeurIPS 2022 An Investigation of the (In)effectiveness of Counterfactually Augmented Data ACL 2022 Anticipating Performativity by Predicting from Predictions NeurIPS 2022 Assaying Out-Of-Distribution Generalization in Transfer Learning NeurIPS 2022 AutoML Two-Sample Test NeurIPS 2022 Beyond the Return: Off-policy Function Estimation under User-specified Error-measuring Distributions NeurIPS 2022 Certifying Some Distributional Fairness with Subpopulation Decomposition NeurIPS 2022 Conformal Prediction with Temporal Quantile Adjustments NeurIPS 2022 Cooperative Distribution Alignment via JSD Upper Bound NeurIPS 2022 DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning NeurIPS 2022 DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation AAAI 2022 Describing Differences between Text Distributions with Natural Language ICML 2022 Distributionally Robust Models with Parametric Likelihood Ratios ICLR 2022 Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift NeurIPS 2022 Estimating and Explaining Model Performance When Both Covariates and Labels Shift NeurIPS 2022 Evaluating Out-of-Distribution Performance on Document Image Classifiers NeurIPS 2022 Evaluating Robustness to Dataset Shift via Parametric Robustness Sets NeurIPS 2022 Fairness Guarantees under Demographic Shift ICLR 2022 How Did the Model Change? Efficiently Assessing Machine Learning API Shifts ICLR 2022 Improving Multi-Task Generalization via Regularizing Spurious Correlation NeurIPS 2022 In the Eye of the Beholder: Robust Prediction with Causal User Modeling NeurIPS 2022 Investigating Data Variance in Evaluations of Automatic Machine Translation Metrics ACL 2022 JAWS: Auditing Predictive Uncertainty Under Covariate Shift NeurIPS 2022 Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding EMNLP 2022 Learning Substructure Invariance for Out-of-Distribution Molecular Representations NeurIPS 2022