Optimal Rates for Random Fourier Features

6 June 2015

Papers citing "Optimal Rates for Random Fourier Features"

36 / 36 papers shown

Title
Tensor Sketch: Fast and Scalable Polynomial Kernel Approximation Ninh Pham Rasmus Pagh 42 0 0 13 May 2025
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 62 0 0 24 Aug 2024
Nyström Kernel Stein Discrepancy Florian Kalinke Zoltan Szabo Bharath K. Sriperumbudur 51 1 0 12 Jun 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
The Representation Jensen-Shannon Divergence J. Hoyos-Osorio Santiago Posso-Murillo L. S. Giraldo 40 6 0 25 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 35 3 0 01 Feb 2023
Compress Then Test: Powerful Kernel Testing in Near-linear Time Carles Domingo-Enrich Raaz Dwivedi Lester W. Mackey 43 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 52 1 0 01 Oct 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
Chefs' Random Tables: Non-Trigonometric Random Features Valerii Likhosherstov K. Choromanski Kumar Avinava Dubey Frederick Liu Tamás Sarlós Adrian Weller 38 17 0 30 May 2022
Maximum Mean Discrepancy on Exponential Windows for Online Change Detection Florian Kalinke Marco Heyden Edouard Fouché Klemens Bohm Klemens Böhm 31 0 0 25 May 2022
SRMD: Sparse Random Mode Decomposition Nicholas Richardson Hayden Schaeffer Giang Tran 27 11 0 12 Apr 2022
A Generalized Weighted Optimization Method for Computational Learning and Inversion Bjorn Engquist Kui Ren Yunan Yang 31 4 0 23 Jan 2022
Global convergence of ResNets: From finite to infinite width using linear parameterization Raphael Barboni Gabriel Peyré Franccois-Xavier Vialard 16 12 0 10 Dec 2021
Bridging the reality gap in quantum devices with physics-aware machine learning D. L. Craig H. Moon F. Fedele D. Lennon B. V. Straaten ... D. Zumbuhl G. Briggs Michael A. Osborne D. Sejdinovic N. Ares 28 13 0 22 Nov 2021
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization Jonathan Wenger Geoff Pleiss Philipp Hennig John P. Cunningham Jacob R. Gardner 22 24 0 01 Jul 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
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 25 110 0 10 Aug 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
Implicit Regularization of Random Feature Models Arthur Jacot Berfin Simsek Francesco Spadaro Clément Hongler Franck Gabriel 31 82 0 19 Feb 2020
COKE: Communication-Censored Decentralized Kernel Learning Ping Xu Yue Wang Xiang Chen Z. Tian 15 20 0 28 Jan 2020
Large-scale Kernel Methods and Applications to Lifelong Robot Learning Raffaello Camoriano 42 1 0 11 Dec 2019
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
Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping Shusen Wang 23 2 0 24 Sep 2019
Sampled Softmax with Random Fourier Features A. S. Rawat Jiecao Chen Felix X. Yu A. Suresh Sanjiv Kumar 39 55 0 24 Jul 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
Domain Generalization by Marginal Transfer Learning Gilles Blanchard A. Deshmukh Ürün Dogan Gyemin Lee Clayton Scott OOD 41 277 0 21 Nov 2017
Differentially Private Database Release via Kernel Mean Embeddings Matej Balog Ilya O. Tolstikhin Bernhard Schölkopf SyDa 45 38 0 04 Oct 2017
Gaussian Quadrature for Kernel Features Tri Dao Christopher De Sa Christopher Ré 36 49 0 08 Sep 2017
Orthogonal Random Features Felix X. Yu A. Suresh K. Choromanski D. Holtmann-Rice Sanjiv Kumar 35 218 0 28 Oct 2016
Operator-Valued Bochner Theorem, Fourier Feature Maps for Operator-Valued Kernels, and Vector-Valued Learning H. Q. Minh 39 18 0 19 Aug 2016
Generalization Properties of Learning with Random Features Alessandro Rudi Lorenzo Rosasco MLT 34 328 0 14 Feb 2016
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families Heiko Strathmann Dino Sejdinovic Samuel Livingstone Z. Szabó Arthur Gretton BDL 24 76 0 08 Jun 2015
Nonparametric sparsity and regularization Lorenzo Rosasco S. Villa S. Mosci M. Santoro A. Verri 93 102 0 13 Aug 2012