Generalization Properties of Learning with Random Features

14 February 2016

Papers citing "Generalization Properties of Learning with Random Features"

50 / 87 papers shown

Title
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Ninh Pham Rasmus Pagh 42 0 0 13 May 2025
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime Francesco Camilli D. Tieplova Eleonora Bergamin Jean Barbier 210 0 0 06 May 2025
Estimating the Spectral Moments of the Kernel Integral Operator from Finite Sample Matrices Chanwoo Chun SueYeon Chung Daniel D. Lee 36 1 0 23 Oct 2024
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 62 0 0 24 Aug 2024
Deep Learning without Global Optimization by Random Fourier Neural Networks Owen Davis Gianluca Geraci Mohammad Motamed BDL 62 0 0 16 Jul 2024
Hyperparameter Optimization for Randomized Algorithms: A Case Study on Random Features Oliver R. A. Dunbar Nicholas H. Nelsen Maya Mutic 48 5 0 30 Jun 2024
Universal randomised signatures for generative time series modelling Francesca Biagini Lukas Gonon Niklas Walter 44 4 0 14 Jun 2024
Deep Sketched Output Kernel Regression for Structured Prediction T. Ahmad Junjie Yang Pierre Laforgue Florence dÁlché-Buc UQCV 47 0 0 13 Jun 2024
Scaling Laws in Linear Regression: Compute, Parameters, and Data Licong Lin Jingfeng Wu Sham Kakade Peter L. Bartlett Jason D. Lee LRM 49 15 0 12 Jun 2024
Overcoming Saturation in Density Ratio Estimation by Iterated Regularization Lukas Gruber Markus Holzleitner Johannes Lehner Sepp Hochreiter Werner Zellinger 56 1 0 21 Feb 2024
Random features models: a way to study the success of naive imputation Alexis Ayme Claire Boyer Lpsm Aymeric Dieuleveut Erwan Scornet 30 3 0 06 Feb 2024
Potential and limitations of random Fourier features for dequantizing quantum machine learning R. Sweke Erik Recio Sofiene Jerbi Elies Gil-Fuster Bryce Fuller Jens Eisert Johannes Jakob Meyer 35 12 0 20 Sep 2023
Universal Approximation Theorem and error bounds for quantum neural networks and quantum reservoirs Lukas Gonon A. Jacquier 43 13 0 24 Jul 2023
Nonlinear Meta-Learning Can Guarantee Faster Rates Dimitri Meunier Zhu Li Arthur Gretton Samory Kpotufe 35 6 0 20 Jul 2023
Error Bounds for Learning with Vector-Valued Random Features S. Lanthaler Nicholas H. Nelsen 29 12 0 26 May 2023
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 40 4 0 23 May 2023
Distributed Gradient Descent for Functional Learning Zhan Yu Jun Fan Zhongjie Shi Ding-Xuan Zhou 23 1 0 12 May 2023
Error analysis of regularized trigonometric linear regression with unbounded sampling: a statistical learning viewpoint Anna Scampicchio Elena Arcari Melanie Zeilinger 27 1 0 16 Mar 2023
When is Importance Weighting Correction Needed for Covariate Shift Adaptation? Davit Gogolashvili Matteo Zecchin Motonobu Kanagawa Marios Kountouris Maurizio Filippone 32 7 0 07 Mar 2023
On the relationship between multivariate splines and infinitely-wide neural networks Francis R. Bach 8 3 0 07 Feb 2023
A Distribution Free Truncated Kernel Ridge Regression Estimator and Related Spectral Analyses Asma Ben Saber Abderrazek Karoui 15 1 0 17 Jan 2023
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 26 4 0 28 Dec 2022
Random Feature Models for Learning Interacting Dynamical Systems Yuxuan Liu S. McCalla Hayden Schaeffer 31 12 0 11 Dec 2022
Vector-Valued Least-Squares Regression under Output Regularity Assumptions Luc Brogat-Motte Alessandro Rudi Céline Brouard Juho Rousu Florence dÁlché-Buc 29 6 0 16 Nov 2022
Unbalanced Optimal Transport, from Theory to Numerics Thibault Séjourné Gabriel Peyré Franccois-Xavier Vialard OT 30 48 0 16 Nov 2022
SPADE4: Sparsity and Delay Embedding based Forecasting of Epidemics Esha Saha L. Ho Giang Tran 38 5 0 11 Nov 2022
RFFNet: Large-Scale Interpretable Kernel Methods via Random Fourier Features Mateus P. Otto Rafael Izbicki 39 1 0 11 Nov 2022
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 170 68 0 27 Oct 2022
Importance Weighting Correction of Regularized Least-Squares for Covariate and Target Shifts Davit Gogolashvili OOD 20 1 0 18 Oct 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 52 1 0 01 Oct 2022
Efficient learning of nonlinear prediction models with time-series privileged information Bastian Jung Fredrik D. Johansson AI4TS 45 5 0 15 Sep 2022
Fast Kernel Methods for Generic Lipschitz Losses via $p$ -Sparsified Sketches T. Ahmad Pierre Laforgue Florence dÁlché-Buc 19 5 0 08 Jun 2022
Randomly Initialized One-Layer Neural Networks Make Data Linearly Separable Promit Ghosal Srinath Mahankali Yihang Sun MLT 29 4 0 24 May 2022
Fast Instrument Learning with Faster Rates Ziyu Wang Yuhao Zhou Jun Zhu 34 3 0 22 May 2022
Concentration of Random Feature Matrices in High-Dimensions Zhijun Chen Hayden Schaeffer Rachel A. Ward 29 6 0 14 Apr 2022
SRMD: Sparse Random Mode Decomposition Nicholas Richardson Hayden Schaeffer Giang Tran 29 11 0 12 Apr 2022
Learning new physics efficiently with nonparametric methods Marco Letizia Gianvito Losapio Marco Rando Gaia Grosso A. Wulzer M. Pierini M. Zanetti Lorenzo Rosasco OOD 31 31 0 05 Apr 2022
Information Theory with Kernel Methods Francis R. Bach 32 40 0 17 Feb 2022
HARFE: Hard-Ridge Random Feature Expansion Esha Saha Hayden Schaeffer Giang Tran 45 14 0 06 Feb 2022
An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings M. Scetbon Laurent Meunier Yaniv Romano 28 10 0 28 Oct 2021
Conditioning of Random Feature Matrices: Double Descent and Generalization Error Zhijun Chen Hayden Schaeffer 39 12 0 21 Oct 2021
Sampling from Arbitrary Functions via PSD Models Ulysse Marteau-Ferey Francis R. Bach Alessandro Rudi 24 10 0 20 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
Random feature neural networks learn Black-Scholes type PDEs without curse of dimensionality Lukas Gonon 26 35 0 14 Jun 2021
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA Nicholas Sterge Bharath K. Sriperumbudur 35 8 0 19 May 2021
Random Features for the Neural Tangent Kernel Insu Han H. Avron N. Shoham Chaewon Kim Jinwoo Shin 27 9 0 03 Apr 2021
Generalization Bounds for Sparse Random Feature Expansions Abolfazl Hashemi Hayden Schaeffer Robert Shi Ufuk Topcu Giang Tran Rachel A. Ward MLT 42 41 0 04 Mar 2021
Learning with invariances in random features and kernel models Song Mei Theodor Misiakiewicz Andrea Montanari OOD 55 89 0 25 Feb 2021
Denoising Score Matching with Random Fourier Features Olga Tsymboi Yermek Kapushev Evgeny Burnaev Ivan Oseledets 39 1 0 13 Jan 2021
Probabilistic Load Forecasting Based on Adaptive Online Learning Verónica Álvarez Santiago Mazuelas Jose A. Lozano 16 61 0 30 Nov 2020