Learning with convolution and pooling operations in kernel methods

v1v2 (latest)

Learning with convolution and pooling operations in kernel methods

16 November 2021

Theodor Misiakiewicz

ArXiv (abs)PDF HTML

Papers citing "Learning with convolution and pooling operations in kernel methods"

16 / 16 papers shown

Title
Locality defeats the curse of dimensionality in convolutional teacher-student scenarios Alessandro Favero Francesco Cagnetta Matthieu Wyart 79 31 0 16 Jun 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 102 91 0 25 Feb 2021
Approximation and Learning with Deep Convolutional Models: a Kernel Perspective A. Bietti 81 30 0 19 Feb 2021
Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration Song Mei Theodor Misiakiewicz Andrea Montanari 89 112 0 26 Jan 2021
The Unreasonable Effectiveness of Patches in Deep Convolutional Kernels Methods L. Thiry Michael Arbel Eugene Belilovsky Edouard Oyallon AAML 56 14 0 19 Jan 2021
Why Are Convolutional Nets More Sample-Efficient than Fully-Connected Nets? Zhiyuan Li Yi Zhang Sanjeev Arora BDL MLT 83 39 0 16 Oct 2020
Computational Separation Between Convolutional and Fully-Connected Networks Eran Malach Shai Shalev-Shwartz 71 26 0 03 Oct 2020
When Do Neural Networks Outperform Kernel Methods? Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari 96 189 0 24 Jun 2020
Enhanced Convolutional Neural Tangent Kernels Zhiyuan Li Ruosong Wang Dingli Yu S. Du Wei Hu Ruslan Salakhutdinov Sanjeev Arora 68 133 0 03 Nov 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 81 243 0 27 Apr 2019
On Lazy Training in Differentiable Programming Lénaïc Chizat Edouard Oyallon Francis R. Bach 111 840 0 19 Dec 2018
Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU Networks Difan Zou Yuan Cao Dongruo Zhou Quanquan Gu ODL 202 448 0 21 Nov 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 233 1,276 0 04 Oct 2018
End-to-End Kernel Learning with Supervised Convolutional Kernel Networks Julien Mairal SSL 68 130 0 20 May 2016
The spectrum of kernel random matrices N. Karoui 173 224 0 04 Jan 2010
Testing for Homogeneity with Kernel Fisher Discriminant Analysis Zaïd Harchaoui Francis R. Bach Eric Moulines 125 119 0 07 Apr 2008

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.