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Intrinsic dimensionality and generalization properties of the $\mathcal{R}$-norm inductive bias


Jun 10, 2022
Clayton Sanford, Navid Ardeshir, Daniel Hsu

* 34 pages 

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Statistical-Computational Trade-offs in Tensor PCA and Related Problems via Communication Complexity


Apr 15, 2022
Rishabh Dudeja, Daniel Hsu


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Masked prediction tasks: a parameter identifiability view


Feb 18, 2022
Bingbin Liu, Daniel Hsu, Pradeep Ravikumar, Andrej Risteski


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Near-Optimal Statistical Query Lower Bounds for Agnostically Learning Intersections of Halfspaces with Gaussian Marginals


Feb 10, 2022
Daniel Hsu, Clayton Sanford, Rocco Servedio, Emmanouil-Vasileios Vlatakis-Gkaragkounis

* 19 pages 

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Learning Tensor Representations for Meta-Learning


Jan 18, 2022
Samuel Deng, Yilin Guo, Daniel Hsu, Debmalya Mandal

* Forthcoming at AISTATS-2022 

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Simple and near-optimal algorithms for hidden stratification and multi-group learning


Dec 22, 2021
Christopher Tosh, Daniel Hsu


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Bayesian decision-making under misspecified priors with applications to meta-learning


Jul 03, 2021
Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire


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Support vector machines and linear regression coincide with very high-dimensional features


May 28, 2021
Navid Ardeshir, Clayton Sanford, Daniel Hsu

* 32 pages, 9 figures 

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Generalization bounds via distillation


Apr 12, 2021
Daniel Hsu, Ziwei Ji, Matus Telgarsky, Lan Wang

* To appear, ICLR 2021 

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On the Approximation Power of Two-Layer Networks of Random ReLUs


Feb 03, 2021
Daniel Hsu, Clayton Sanford, Rocco A. Servedio, Emmanouil-Vasileios Vlatakis-Gkaragkounis


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