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Statistical Learning

4076 directly classified papers

Papers per year

Papers

Interpolating Classifiers Make Few Mistakes JMLR 2023
Revisiting Fair-PAC Learning and the Axioms of Cardinal Welfare AISTATS 2023
Robust and Agnostic Learning of Conditional Distributional Treatment Effects AISTATS 2023
PAC-Bayesian Learning of Optimization Algorithms AISTATS 2023
Is interpolation benign for random forest regression? AISTATS 2023
Privacy-preserving Sparse Generalized Eigenvalue Problem AISTATS 2023
A Reinforcement Learning Framework for Dynamic Mediation Analysis ICML 2023
Bayesian Strategy-Proof Facility Location via Robust Estimation AISTATS 2023
On the bias of K-fold cross validation with stable learners AISTATS 2023
Byzantine-Robust Federated Learning with Optimal Statistical Rates AISTATS 2023
Multi-armed Bandit Experimental Design: Online Decision-making and Adaptive Inference AISTATS 2023
Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions ICML 2023
Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group AISTATS 2023
“Plus/minus the learning rate”: Easy and Scalable Statistical Inference with SGD AISTATS 2023
Statistical Indistinguishability of Learning Algorithms ICML 2023
Mixed-Effect Thompson Sampling AISTATS 2023
Fixing by Mixing: A Recipe for Optimal Byzantine ML under Heterogeneity AISTATS 2023
Optimal and Private Learning from Human Response Data AISTATS 2023
On the Capacity Limits of Privileged ERM AISTATS 2023
Instance-Dependent Generalization Bounds via Optimal Transport JMLR 2023
Semi-Verified PAC Learning from the Crowd AISTATS 2023
A Likelihood Approach to Nonparametric Estimation of a Singular Distribution Using Deep Generative Models JMLR 2023
A Case of Exponential Convergence Rates for SVM AISTATS 2023
Data-OOB: Out-of-bag Estimate as a Simple and Efficient Data Value ICML 2023
Model-X Sequential Testing for Conditional Independence via Testing by Betting AISTATS 2023