On the Error of Random Fourier Features

9 June 2015

Papers citing "On the Error of Random Fourier Features"

37 / 37 papers shown

Title
Random feature-based double Vovk-Azoury-Warmuth algorithm for online multi-kernel learning Dmitry B. Rokhlin Olga V. Gurtovaya 50 0 0 25 Mar 2025
Fast Summation of Radial Kernels via QMC Slicing Johannes Hertrich Tim Jahn Michael Quellmalz 26 5 0 02 Oct 2024
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 57 0 0 24 Aug 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes J. Lin Shreyas Padhy Bruno Mlodozeniec Javier Antorán José Miguel Hernández-Lobato 43 2 0 28 May 2024
Dynamic Online Ensembles of Basis Expansions Daniel Waxman Petar M. Djurić 45 4 0 02 May 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 30 12 0 20 Sep 2023
On the Size and Approximation Error of Distilled Sets Alaa Maalouf M. Tukan Noel Loo Ramin Hasani Mathias Lechner Daniela Rus DD 38 4 0 23 May 2023
FAVOR#: Sharp Attention Kernel Approximations via New Classes of Positive Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 23 3 0 01 Feb 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time Carles Domingo-Enrich Raaz Dwivedi Lester W. Mackey 41 9 0 14 Jan 2023
Provably Reliable Large-Scale Sampling from Gaussian Processes Anthony Stephenson Robert Allison Edward O. Pyzer-Knapp 24 2 0 15 Nov 2022
On The Relative Error of Random Fourier Features for Preserving Kernel Distance Kuan Cheng S. Jiang Luojian Wei Zhide Wei 47 1 0 01 Oct 2022
Random Fourier Features for Asymmetric Kernels Ming-qian He Fan He Fanghui Liu Xiaolin Huang 28 3 0 18 Sep 2022
Neural Implicit Dictionary via Mixture-of-Expert Training Peihao Wang Zhiwen Fan Tianlong Chen Zhangyang Wang 25 12 0 08 Jul 2022
Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 33 17 0 30 May 2022
Relaxing Equivariance Constraints with Non-stationary Continuous Filters Tycho F. A. van der Ouderaa David W. Romero Mark van der Wilk 24 32 0 14 Apr 2022
Transparent Single-Cell Set Classification with Kernel Mean Embeddings Siyuan Shan Vishal Baskaran Haidong Yi Jolene S Ranek Natalie Stanley Junier Oliva 24 11 0 18 Jan 2022
Vector-valued Gaussian Processes on Riemannian Manifolds via Gauge Independent Projected Kernels M. Hutchinson Alexander Terenin Viacheslav Borovitskiy So Takao Yee Whye Teh M. Deisenroth 28 20 0 27 Oct 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
Bias-Free Scalable Gaussian Processes via Randomized Truncations Andres Potapczynski Luhuan Wu D. Biderman Geoff Pleiss John P. Cunningham 12 19 0 12 Feb 2021
Nonlinear Distribution Regression for Remote Sensing Applications J. Adsuara Adrián Pérez-Suay Jordi Munoz-Marí Anna Mateo-Sanchis M. Piles Gustau Camps-Valls 23 17 0 07 Dec 2020
Pathwise Conditioning of Gaussian Processes James T. Wilson Viacheslav Borovitskiy Alexander Terenin P. Mostowsky M. Deisenroth 18 58 0 08 Nov 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
DP-MERF: Differentially Private Mean Embeddings with Random Features for Practical Privacy-Preserving Data Generation Frederik Harder Kamil Adamczewski Mijung Park SyDa 25 101 0 26 Feb 2020
COKE: Communication-Censored Decentralized Kernel Learning Ping Xu Yue Wang Xiang Chen Z. Tian 15 20 0 28 Jan 2020
Gaussian Processes with Errors in Variables: Theory and Computation Shuang Zhou D. Pati Tianying Wang Yun Yang R. Carroll 27 3 0 14 Oct 2019
Approximating Spectral Clustering via Sampling: a Review Nicolas M Tremblay Andreas Loukas 21 45 0 29 Jan 2019
On Kernel Derivative Approximation with Random Fourier Features Z. Szabó Bharath K. Sriperumbudur 32 12 0 11 Oct 2018
Random Feature Stein Discrepancies Jonathan H. Huggins Lester W. Mackey 35 45 0 20 Jun 2018
Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features Minh-Nghia Nguyen Ngo Anh Vien 4 34 0 13 Apr 2018
Domain Generalization by Marginal Transfer Learning Gilles Blanchard A. Deshmukh Ürün Dogan Gyemin Lee Clayton Scott OOD 41 275 0 21 Nov 2017
Gaussian Quadrature for Kernel Features Tri Dao Christopher De Sa Christopher Ré 30 49 0 08 Sep 2017
Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features P. Bouboulis S. Chouvardas Sergios Theodoridis 34 69 0 23 Mar 2017
Approximate Kernel-based Conditional Independence Tests for Fast Non-Parametric Causal Discovery Eric V. Strobl Kun Zhang Shyam Visweswaran BDL 34 170 0 13 Feb 2017
Operator-Valued Bochner Theorem, Fourier Feature Maps for Operator-Valued Kernels, and Vector-Valued Learning H. Q. Minh 30 18 0 19 Aug 2016
Linearized GMM Kernels and Normalized Random Fourier Features Ping Li 30 9 0 18 May 2016
Bayesian Nonparametric Kernel-Learning Junier Oliva Kumar Avinava Dubey A. Wilson Barnabás Póczós J. Schneider Eric Xing BDL 24 71 0 29 Jun 2015
Optimal Rates for Random Fourier Features Bharath K. Sriperumbudur Z. Szabó 23 128 0 06 Jun 2015