Conditioning of Random Feature Matrices: Double Descent and Generalization Error

21 October 2021

Papers citing "Conditioning of Random Feature Matrices: Double Descent and Generalization Error"

29 / 29 papers shown

Title
Generalization Bounds for Sparse Random Feature Expansions Abolfazl Hashemi Hayden Schaeffer Robert Shi Ufuk Topcu Giang Tran Rachel A. Ward MLT 122 41 0 04 Mar 2021
Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration Song Mei Theodor Misiakiewicz Andrea Montanari 71 111 0 26 Jan 2021
Avoiding The Double Descent Phenomenon of Random Feature Models Using Hybrid Regularization Kelvin K. Kan J. Nagy Lars Ruthotto AI4CE 61 6 0 11 Dec 2020
Benign overfitting in ridge regression Alexander Tsigler Peter L. Bartlett 66 166 0 29 Sep 2020
Towards a Mathematical Understanding of Neural Network-Based Machine Learning: what we know and what we don't E. Weinan Chao Ma Stephan Wojtowytsch Lei Wu AI4CE 69 134 0 22 Sep 2020
The Slow Deterioration of the Generalization Error of the Random Feature Model Chao Ma Lei Wu E. Weinan 68 15 0 13 Aug 2020
A Random Matrix Analysis of Random Fourier Features: Beyond the Gaussian Kernel, a Precise Phase Transition, and the Corresponding Double Descent Zhenyu Liao Romain Couillet Michael W. Mahoney 69 89 0 09 Jun 2020
On Random Matrices Arising in Deep Neural Networks. Gaussian Case L. Pastur 46 23 0 17 Jan 2020
Double descent in the condition number T. Poggio Gil Kur Andy Banburski 42 27 0 12 Dec 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 80 634 0 14 Aug 2019
NeuPDE: Neural Network Based Ordinary and Partial Differential Equations for Modeling Time-Dependent Data Yifan Sun Linan Zhang Hayden Schaeffer AI4TS 44 91 0 08 Aug 2019
Benign Overfitting in Linear Regression Peter L. Bartlett Philip M. Long Gábor Lugosi Alexander Tsigler MLT 67 777 0 26 Jun 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 157 743 0 19 Mar 2019
Two models of double descent for weak features M. Belkin Daniel J. Hsu Ji Xu 85 376 0 18 Mar 2019
Reconciling modern machine learning practice and the bias-variance trade-off M. Belkin Daniel J. Hsu Siyuan Ma Soumik Mandal 197 1,638 0 28 Dec 2018
Forward Stability of ResNet and Its Variants Linan Zhang Hayden Schaeffer 82 47 0 24 Nov 2018
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize Tengyuan Liang Alexander Rakhlin 58 353 0 01 Aug 2018
Does data interpolation contradict statistical optimality? M. Belkin Alexander Rakhlin Alexandre B. Tsybakov 71 219 0 25 Jun 2018
On the Spectrum of Random Features Maps of High Dimensional Data Zhenyu Liao Romain Couillet 42 51 0 30 May 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 202 3,457 0 09 Mar 2018
To understand deep learning we need to understand kernel learning M. Belkin Siyuan Ma Soumik Mandal 55 418 0 05 Feb 2018
Resurrecting the sigmoid in deep learning through dynamical isometry: theory and practice Jeffrey Pennington S. Schoenholz Surya Ganguli ODL 43 252 0 13 Nov 2017
High-dimensional dynamics of generalization error in neural networks Madhu S. Advani Andrew M. Saxe AI4CE 128 469 0 10 Oct 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 120 727 0 09 May 2017
A Random Matrix Approach to Neural Networks Cosme Louart Zhenyu Liao Romain Couillet 62 161 0 17 Feb 2017
Generalization Properties of Learning with Random Features Alessandro Rudi Lorenzo Rosasco MLT 68 331 0 14 Feb 2016
The Spectral Norm of Random Inner-Product Kernel Matrices Z. Fan Andrea Montanari 84 47 0 19 Jul 2015
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 43 277 0 16 Jul 2015
The spectrum of kernel random matrices N. Karoui 146 224 0 04 Jan 2010