Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration

26 January 2021

Papers citing "Generalization error of random features and kernel methods: hypercontractivity and kernel matrix concentration"

32 / 32 papers shown

Title
Sobolev norm inconsistency of kernel interpolation Yunfei Yang 39 0 0 29 Apr 2025
Beyond Benign Overfitting in Nadaraya-Watson Interpolators Daniel Barzilai Guy Kornowski Ohad Shamir 83 0 0 11 Feb 2025
Overfitting Behaviour of Gaussian Kernel Ridgeless Regression: Varying Bandwidth or Dimensionality Marko Medvedev Gal Vardi Nathan Srebro 70 3 0 05 Sep 2024
Universal randomised signatures for generative time series modelling Francesca Biagini Lukas Gonon Niklas Walter 49 4 0 14 Jun 2024
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum Tin Sum Cheng Aurelien Lucchi Anastasis Kratsios David Belius 45 8 0 02 Feb 2024
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs Lukas Gonon A. Jacquier 43 13 0 24 Jul 2023
Error Bounds for Learning with Vector-Valued Random Features S. Lanthaler Nicholas H. Nelsen 32 12 0 26 May 2023
Least Squares Regression Can Exhibit Under-Parameterized Double Descent Xinyue Li Rishi Sonthalia 49 3 0 24 May 2023
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks Eshaan Nichani Alexandru Damian Jason D. Lee MLT 50 13 0 11 May 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 51 0 0 24 Mar 2023
Learning time-scales in two-layers neural networks Raphael Berthier Andrea Montanari Kangjie Zhou 41 33 0 28 Feb 2023
Bayes-optimal Learning of Deep Random Networks of Extensive-width Hugo Cui Florent Krzakala Lenka Zdeborová BDL 30 35 0 01 Feb 2023
Strong inductive biases provably prevent harmless interpolation Michael Aerni Marco Milanta Konstantin Donhauser Fanny Yang 42 9 0 18 Jan 2023
Random Feature Models for Learning Interacting Dynamical Systems Yuxuan Liu S. McCalla Hayden Schaeffer 31 12 0 11 Dec 2022
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 170 68 0 27 Oct 2022
A Universal Trade-off Between the Model Size, Test Loss, and Training Loss of Linear Predictors Nikhil Ghosh M. Belkin 24 7 0 23 Jul 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials Eshaan Nichani Yunzhi Bai Jason D. Lee 29 10 0 08 Jun 2022
Sharp Asymptotics of Kernel Ridge Regression Beyond the Linear Regime Hong Hu Yue M. Lu 53 15 0 13 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 47 121 0 03 May 2022
SRMD: Sparse Random Mode Decomposition Nicholas Richardson Hayden Schaeffer Giang Tran 29 11 0 12 Apr 2022
HARFE: Hard-Ridge Random Feature Expansion Esha Saha Hayden Schaeffer Giang Tran 48 14 0 06 Feb 2022
Learning with convolution and pooling operations in kernel methods Theodor Misiakiewicz Song Mei MLT 20 29 0 16 Nov 2021
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 42 12 0 21 Oct 2021
Deformed semicircle law and concentration of nonlinear random matrices for ultra-wide neural networks Zhichao Wang Yizhe Zhu 40 18 0 20 Sep 2021
Reconstruction on Trees and Low-Degree Polynomials Frederic Koehler Elchanan Mossel 35 9 0 14 Sep 2021
A Farewell to the Bias-Variance Tradeoff? An Overview of the Theory of Overparameterized Machine Learning Yehuda Dar Vidya Muthukumar Richard G. Baraniuk 41 71 0 06 Sep 2021
Deep Networks Provably Classify Data on Curves Tingran Wang Sam Buchanan D. Gilboa John N. Wright 28 9 0 29 Jul 2021
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality Lukas Gonon 26 35 0 14 Jun 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 55 89 0 25 Feb 2021
The Interpolation Phase Transition in Neural Networks: Memorization and Generalization under Lazy Training Andrea Montanari Yiqiao Zhong 49 95 0 25 Jul 2020
Random Features for Kernel Approximation: A Survey on Algorithms, Theory, and Beyond Fanghui Liu Xiaolin Huang Yudong Chen Johan A. K. Suykens BDL 51 172 0 23 Apr 2020
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 88 281 0 09 Aug 2012