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Ilias Diakonikolas
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Efficient Testable Learning of Halfspaces with Adversarial Label Noise


Mar 09, 2023
Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Sihan Liu, Nikos Zarifis

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Near-Optimal Cryptographic Hardness of Agnostically Learning Halfspaces and ReLU Regression under Gaussian Marginals


Feb 13, 2023
Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren

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A Nearly Tight Bound for Fitting an Ellipsoid to Gaussian Random Points


Dec 21, 2022
Daniel M. Kane, Ilias Diakonikolas

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A Strongly Polynomial Algorithm for Approximate Forster Transforms and its Application to Halfspace Learning


Dec 06, 2022
Ilias Diakonikolas, Christos Tzamos, Daniel M. Kane

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Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions


Nov 29, 2022
Ilias Diakonikolas, Daniel M. Kane, Jasper C. H. Lee, Ankit Pensia

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* To appear in NeurIPS 2022 
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Gaussian Mean Testing Made Simple


Oct 25, 2022
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia

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* To appear in SIAM Symposium on Simplicity in Algorithms (SOSA) 2023 
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SQ Lower Bounds for Learning Single Neurons with Massart Noise


Oct 18, 2022
Ilias Diakonikolas, Daniel M. Kane, Lisheng Ren, Yuxin Sun

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* To appear in NeurIPS 2022 
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Cryptographic Hardness of Learning Halfspaces with Massart Noise


Jul 28, 2022
Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi, Lisheng Ren

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Near-Optimal Bounds for Testing Histogram Distributions


Jul 14, 2022
Clément L. Canonne, Ilias Diakonikolas, Daniel M. Kane, Sihan Liu

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Learning a Single Neuron with Adversarial Label Noise via Gradient Descent


Jun 17, 2022
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis

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