Statistics

Wasserstein F-tests for Frechet regression on Bures-Wasserstein manifolds JMLR 2025 Adjust Pearson's r to Measure Arbitrary Monotone Dependence NeurIPS 2024 Analysis of Differentially Private Synthetic Data: A Measurement Error Approach AAAI 2024 A two-scale Complexity Measure for Deep Learning Models NeurIPS 2024 Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) COLT 2024 Conformalized Multiple Testing after Data-dependent Selection NeurIPS 2024 Controlling Multiple Errors Simultaneously with a PAC-Bayes Bound NeurIPS 2024 Covariate Shift Corrected Conditional Randomization Test NeurIPS 2024 Data Thinning for Convolution-Closed Distributions JMLR 2024 Differentially Private Equivalence Testing for Continuous Distributions and Applications NeurIPS 2024 Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers NeurIPS 2024 Distributed Gaussian Mean Estimation under Communication Constraints: Optimal Rates and Communication-Efficient Algorithms JMLR 2024 Equivalence Testing: The Power of Bounded Adaptivity AISTATS 2024 False discovery proportion envelopes with m-consistency JMLR 2024 Flat Minima in Linear Estimation and an Extended Gauss Markov Theorem ICLR 2024 Hierarchical and Density-based Causal Clustering NeurIPS 2024 Instance-Optimal Private Density Estimation in the Wasserstein Distance NeurIPS 2024 Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance? NeurIPS 2024 Low Degree Hardness for Broadcasting on Trees NeurIPS 2024 Mean-Square Analysis of Discretized Itô Diffusions for Heavy-tailed Sampling JMLR 2024 Near-Optimality of Contrastive Divergence Algorithms NeurIPS 2024 Nonparametric Copula Models for Multivariate, Mixed, and Missing Data JMLR 2024 Nonparametric Inference under B-bits Quantization JMLR 2024 Nonparametric Regression for 3D Point Cloud Learning JMLR 2024 On Differentially Private U Statistics NeurIPS 2024