agnostic learning

Provable guarantees for decision tree induction: the agnostic setting ICML 2020 Statistical-Query Lower Bounds via Functional Gradients NeurIPS 2020 A Sharp Lower Bound for Agnostic Learning with Sample Compression Schemes ALT 2019 Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds COLT 2019 Limits of Private Learning with Access to Public Data NeurIPS 2019 Nearly Tight Bounds for Robust Proper Learning of Halfspaces with a Margin NeurIPS 2019 Sum-of-squares meets square loss: Fast rates for agnostic tensor completion COLT 2019 Optimal Quantum Sample Complexity of Learning Algorithms JMLR 2018 Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness ICML 2018 Lifelong Learning in Costly Feature Spaces ALT 2017 Active Learning with Oracle Epiphany NeurIPS 2016 Communication Efficient Distributed Agnostic Boosting AISTATS 2016 Complexity Theoretic Limitations on Learning DNF’s COLT 2016 Supervised learning through the lens of compression NeurIPS 2016 Agnostic Learning of Disjunctions on Symmetric Distributions JMLR 2015 A PTAS for Agnostically Learning Halfspaces COLT 2015 Classification with Low Rank and Missing Data ICML 2015 Efficient and Parsimonious Agnostic Active Learning NeurIPS 2015 The Sample Complexity of Learning Linear Predictors with the Squared Loss JMLR 2015 A Boosting Framework on Grounds of Online Learning NeurIPS 2014 Beyond Disagreement-Based Agnostic Active Learning NeurIPS 2014 Distribution-independent Reliable Learning COLT 2014 Learning Coverage Functions and Private Release of Marginals COLT 2014 New Results for Random Walk Learning JMLR 2014 The sample complexity of agnostic learning under deterministic labels COLT 2014