On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels

27 August 2019

Papers citing "On the Multiple Descent of Minimum-Norm Interpolants and Restricted Lower Isometry of Kernels"

11 / 11 papers shown

Title
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 46 89 0 25 Feb 2021
Deep Equals Shallow for ReLU Networks in Kernel Regimes A. Bietti Francis R. Bach 28 86 0 30 Sep 2020
Interpolation and Learning with Scale Dependent Kernels Nicolò Pagliana Alessandro Rudi E. De Vito Lorenzo Rosasco 44 8 0 17 Jun 2020
Spectra of the Conjugate Kernel and Neural Tangent Kernel for linear-width neural networks Z. Fan Zhichao Wang 44 71 0 25 May 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 44 172 0 23 Apr 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 33 68 0 05 Feb 2020
A Constructive Prediction of the Generalization Error Across Scales Jonathan S. Rosenfeld Amir Rosenfeld Yonatan Belinkov Nir Shavit 30 205 0 27 Sep 2019
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization T. Poggio Andrzej Banburski Q. Liao ODL 29 161 0 25 Aug 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 18 241 0 27 Apr 2019
Small ReLU networks are powerful memorizers: a tight analysis of memorization capacity Chulhee Yun S. Sra Ali Jadbabaie 23 117 0 17 Oct 2018
Learning without Concentration S. Mendelson 85 333 0 01 Jan 2014