statistical query

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 Robust Sparse Mean Estimation via Sum of Squares COLT 2022 SQ Lower Bounds for Learning Single Neurons with Massart Noise NeurIPS 2022 Differentially Private Query Release Through Adaptive Projection ICML 2021 Efficient Algorithms for Learning from Coarse Labels COLT 2021 Leveraging Public Data for Practical Private Query Release ICML 2021 On the Power of Differentiable Learning versus PAC and SQ Learning NeurIPS 2021 Robust Learning under Strong Noise via SQs AISTATS 2021 Statistical Query Algorithms and Low Degree Tests Are Almost Equivalent COLT 2021 Statistical Query Lower Bounds for List-Decodable Linear Regression NeurIPS 2021 The Optimality of Polynomial Regression for Agnostic Learning under Gaussian Marginals in the SQ Model COLT 2021 Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis AISTATS 2020 Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals NeurIPS 2020 New Oracle-Efficient Algorithms for Private Synthetic Data Release ICML 2020 Sampling Without Compromising Accuracy in Adaptive Data Analysis ALT 2020 Statistical-Query Lower Bounds via Functional Gradients NeurIPS 2020 Towards a Combinatorial Characterization of Bounded-Memory Learning NeurIPS 2020 Adversarial examples from computational constraints ICML 2019 Gradient Descent for One-Hidden-Layer Neural Networks: Polynomial Convergence and SQ Lower Bounds COLT 2019 On Mean Estimation for General Norms with Statistical Queries COLT 2019 Calibrating Noise to Variance in Adaptive Data Analysis COLT 2018 The Limits of Post-Selection Generalization NeurIPS 2018 A General Characterization of the Statistical Query Complexity COLT 2017 Dealing with Range Anxiety in Mean Estimation via Statistical Queries ALT 2017