proper learning

Refining the Sample Complexity of Comparative Learning ALT 2025 Learning bounded-degree polytrees with known skeleton ALT 2024 Learning Noisy Halfspaces with a Margin: Massart is No Harder than Random NeurIPS 2024 Find a witness or shatter: the landscape of computable PAC learning. COLT 2023 On Proper Learnability between Average- and Worst-case Robustness NeurIPS 2023 Open Problem: Properly learning decision trees in polynomial time? COLT 2022 Optimal Dynamic Regret in Proper Online Learning with Strongly Convex Losses and Beyond AISTATS 2022 Agnostic Proper Learning of Halfspaces under Gaussian Marginals COLT 2021 Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games COLT 2021 Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020 The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise NeurIPS 2020 Average-Case Information Complexity of Learning ALT 2019 Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin NeurIPS 2019 On Communication Complexity of Classification Problems COLT 2019 Hardness of Learning Noisy Halfspaces using Polynomial Thresholds COLT 2018 Learning convex polytopes with margin NeurIPS 2018 Robust and Proper Learning for Mixtures of Gaussians via Systems of Polynomial Inequalities COLT 2017 Properly Learning Poisson Binomial Distributions in Almost Polynomial Time COLT 2016 Optimal Testing for Properties of Distributions NeurIPS 2015 Faster and Sample Near-Optimal Algorithms for Proper Learning Mixtures of Gaussians COLT 2014 Tight Bounds on Proper Equivalence Query Learning of DNF COLT 2012 Negative Results for Active Learning with Convex Losses AISTATS 2010