Statistics

A Proposal for Scaling the Scaling Laws EACL 2024 Arctique: An artificial histopathological dataset unifying realism and controllability for uncertainty quantification NeurIPS 2024 A Separation in Heavy-Tailed Sampling: Gaussian vs. Stable Oracles for Proximal Samplers NeurIPS 2024 Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning ICLR 2024 A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems NeurIPS 2024 Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm NeurIPS 2024 Beyond Catoni: Sharper Rates for Heavy-Tailed and Robust Mean Estimation COLT 2024 Boosted Conformal Prediction Intervals NeurIPS 2024 Breaking the curse of dimensionality in structured density estimation NeurIPS 2024 Choosing the p in Lp Loss: Adaptive Rates for Symmetric Mean Estimation COLT 2024 Cluster-Adaptive Network A/B Testing: From Randomization to Estimation JMLR 2024 Confident Feature Ranking AISTATS 2024 Conformalized Multiple Testing after Data-dependent Selection NeurIPS 2024 CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models EMNLP 2024 Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NeurIPS 2024 Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning AISTATS 2024 Covariate Shift Corrected Conditional Randomization Test NeurIPS 2024 Coverage-Guaranteed Prediction Sets for Out-of-Distribution Data AAAI 2024 Data-Driven Confidence Intervals with Optimal Rates for the Mean of Heavy-Tailed Distributions AISTATS 2024 Decorrelated Variable Importance JMLR 2024 Deep anytime-valid hypothesis testing AISTATS 2024 DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection NeurIPS 2024 Detecting critical treatment effect bias in small subgroups UAI 2024 Differentially Private Equivalence Testing for Continuous Distributions and Applications NeurIPS 2024 Dimension-free Structured Covariance Estimation COLT 2024