improper learning

Group-realizable multi-group learning by minimizing empirical risk ALT 2026 Computational-Statistical Gaps for Improper Learning in Sparse Linear Regression COLT 2024 Improved Hardness Results for Learning Intersections of Halfspaces COLT 2024 Find a witness or shatter: the landscape of computable PAC learning. COLT 2023 On characterizations of learnability with computable learners COLT 2022 On Optimal Learning Under Targeted Data Poisoning NeurIPS 2022 Localization, Convexity, and Star Aggregation NeurIPS 2021 Misspecification in Prediction Problems and Robustness via Improper Learning AISTATS 2021 Classification Under Misspecification: Halfspaces, Generalized Linear Models, and Evolvability NeurIPS 2020 Efficient improper learning for online logistic regression COLT 2020 Proper Learning, Helly Number, and an Optimal SVM Bound COLT 2020 Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs ALT 2019 The Optimal Approximation Factor in Density Estimation COLT 2019 VC Classes are Adversarially Robustly Learnable, but Only Improperly COLT 2019 Actively Avoiding Nonsense in Generative Models COLT 2018 Logistic Regression: The Importance of Being Improper COLT 2018 Online Improper Learning with an Approximation Oracle NeurIPS 2018 Open problem: Improper learning of mixtures of Gaussians COLT 2018 Learning Linear Dynamical Systems via Spectral Filtering NeurIPS 2017 Improper Deep Kernels AISTATS 2016 L1-regularized Neural Networks are Improperly Learnable in Polynomial Time ICML 2016 Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints COLT 2015 Optimal learners for multiclass problems COLT 2014