Statistical Learning

Estimating Causal Effects Identifiable from a Combination of Observations and Experiments NeurIPS 2023 Estimating Heterogeneous Treatment Effects: Mutual Information Bounds and Learning Algorithms ICML 2023 Estimating Noise Correlations Across Continuous Conditions With Wishart Processes NeurIPS 2023 Estimation Beyond Data Reweighting: Kernel Method of Moments ICML 2023 Evaluating and reducing the distance between synthetic and real speech distributions Interspeech 2023 Evaluating Generative Networks Using Gaussian Mixtures of Image Features WACV 2023 Evaluating Instrument Validity using the Principle of Independent Mechanisms JMLR 2023 Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts NeurIPS 2023 Evaluating the Moral Beliefs Encoded in LLMs NeurIPS 2023 Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model NeurIPS 2023 Explainability as statistical inference ICML 2023 Exploring Local Norms in Exp-concave Statistical Learning COLT 2023 Exploring the Relationship between Alignment and Cross-lingual Transfer in Multilingual Transformers ACL 2023 Exponential Generalization Bounds with Near-Optimal Rates for L_q-Stable Algorithms ICLR 2023 Extending Conformal Prediction to Hidden Markov Models with Exact Validity via de Finetti’s Theorem for Markov Chains ICML 2023 Facial Expression Recognition with Adaptive Frame Rate based on Multiple Testing Correction ICML 2023 Fair Survival Time Prediction via Mutual Information Minimization MLHC 2023 Faithful Model Evaluation for Model-Based Metrics EMNLP 2023 False Discovery Proportion control for aggregated Knockoffs NeurIPS 2023 Falsification of Internal and External Validity in Observational Studies via Conditional Moment Restrictions AISTATS 2023 Fast and scalable score-based kernel calibration tests UAI 2023 Fast Counterfactual Inference for History-Based Reinforcement Learning AAAI 2023 Fast Excess Risk Rates via Offset Rademacher Complexity ICML 2023 Fast Expectation Propagation for Heteroscedastic, Lasso-Penalized, and Quantile Regression JMLR 2023 Feature Likelihood Divergence: Evaluating the Generalization of Generative Models Using Samples NeurIPS 2023