Statistical Learning

Optimal Mean Estimation without a Variance COLT 2022 Optimal partition recovery in general graphs AISTATS 2022 Optimal Rates for Regularized Conditional Mean Embedding Learning NeurIPS 2022 Optimal SQ Lower Bounds for Learning Halfspaces with Massart Noise COLT 2022 Optimal SQ Lower Bounds for Robustly Learning Discrete Product Distributions and Ising Models COLT 2022 Original or Translated? A Causal Analysis of the Impact of Translationese on Machine Translation Performance NAACL 2022 Orthogonal Statistical Learning with Self-Concordant Loss COLT 2022 Outlier-Robust Sparse Estimation via Non-Convex Optimization NeurIPS 2022 Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions NeurIPS 2022 PAC-Bayesian Bounds on Rate-Efficient Classifiers ICML 2022 PAC Learning of Quantum Measurement Classes : Sample Complexity Bounds and Universal Consistency AISTATS 2022 PACm-Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime AISTATS 2022 Pairwise Fairness for Ordinal Regression AISTATS 2022 Parametric Bootstrap for Differentially Private Confidence Intervals AISTATS 2022 Perceptual Evaluation of Penetrating Voices through a Semantic Differential Method Interspeech 2022 Pre-activation Distributions Expose Backdoor Neurons NeurIPS 2022 Precise Learning Curves and Higher-Order Scalings for Dot-product Kernel Regression NeurIPS 2022 Privacy Induces Robustness: Information-Computation Gaps and Sparse Mean Estimation NeurIPS 2022 Private and Communication-Efficient Algorithms for Entropy Estimation NeurIPS 2022 Private and polynomial time algorithms for learning Gaussians and beyond COLT 2022 Private Estimation with Public Data NeurIPS 2022 Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size AISTATS 2022 Probable Domain Generalization via Quantile Risk Minimization NeurIPS 2022 Provable Generalization of Overparameterized Meta-learning Trained with SGD NeurIPS 2022 Provably Confidential Language Modelling NAACL 2022