Interpolating Classifiers Make Few Mistakes

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Interpolating Classifiers Make Few Mistakes

28 January 2021

Benjamin Recht

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Papers citing "Interpolating Classifiers Make Few Mistakes"

17 / 17 papers shown

Title
Classification vs regression in overparameterized regimes: Does the loss function matter? Vidya Muthukumar Adhyyan Narang Vignesh Subramanian M. Belkin Daniel J. Hsu A. Sahai 89 151 0 16 May 2020
Compressive sensing with un-trained neural networks: Gradient descent finds the smoothest approximation Reinhard Heckel Mahdi Soltanolkotabi 61 81 0 07 May 2020
Finite-sample Analysis of Interpolating Linear Classifiers in the Overparameterized Regime Niladri S. Chatterji Philip M. Long 46 108 0 25 Apr 2020
Neural Kernels Without Tangents Vaishaal Shankar Alex Fang Wenshuo Guo Sara Fridovich-Keil Ludwig Schmidt Jonathan Ragan-Kelley Benjamin Recht 46 91 0 04 Mar 2020
$A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum-$\ell_1$-Norm Interpolated Classifiers$ A Precise High-Dimensional Asymptotic Theory for Boosting and Minimum- $\ell_1$ -Norm Interpolated Classifiers Tengyuan Liang Pragya Sur 79 70 0 05 Feb 2020
A Model of Double Descent for High-dimensional Binary Linear Classification Zeyu Deng A. Kammoun Christos Thrampoulidis 85 146 0 13 Nov 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 86 776 0 26 Jun 2019
Exact Gaussian Processes on a Million Data Points Ke Alexander Wang Geoff Pleiss Jacob R. Gardner Stephen Tyree Kilian Q. Weinberger A. Wilson GP 55 230 0 19 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 194 743 0 19 Mar 2019
numpywren: serverless linear algebra Vaishaal Shankar K. Krauth Qifan Pu Eric Jonas Shivaram Venkataraman Ion Stoica Benjamin Recht Jonathan Ragan-Kelley 60 110 0 23 Oct 2018
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize Tengyuan Liang Alexander Rakhlin 65 354 0 01 Aug 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 267 3,203 0 20 Jun 2018
FALKON: An Optimal Large Scale Kernel Method Alessandro Rudi Luigi Carratino Lorenzo Rosasco 78 196 0 31 May 2017
Diving into the shallows: a computational perspective on large-scale shallow learning Siyuan Ma M. Belkin 64 78 0 30 Mar 2017
Faster Kernel Ridge Regression Using Sketching and Preconditioning H. Avron K. Clarkson David P. Woodruff 73 125 0 10 Nov 2016
Optimistic Rates for Learning with a Smooth Loss Nathan Srebro Karthik Sridharan Ambuj Tewari 160 283 0 20 Sep 2010
The spectrum of kernel random matrices N. Karoui 162 224 0 04 Jan 2010