Kernel methods through the roof: handling billions of points efficiently

18 June 2020

Papers citing "Kernel methods through the roof: handling billions of points efficiently"

25 / 25 papers shown

Title
Learning cardiac activation and repolarization times with operator learning Edoardo Centofanti Giovanni Ziarelli N. Parolini Simone Scacchi M. Verani L. Pavarino AI4CE 31 0 0 13 May 2025
Forecasting time series with constraints Nathan Doumèche Francis Bach Éloi Bedek Gérard Biau Claire Boyer Y. Goude AI4TS 45 0 0 14 Feb 2025
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky Ethan N. Epperly J. Tropp R. Webber 34 3 0 04 Oct 2024
Learning in Feature Spaces via Coupled Covariances: Asymmetric Kernel SVD and Nyström method Qinghua Tao F. Tonin Alex Lambert Yingyi Chen Panagiotis Patrinos Johan A. K. Suykens 40 1 0 13 Jun 2024
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio Lyudmila Grigoryeva M. Tamborrino 35 1 0 20 May 2024
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning Michal Dereziñski Christopher Musco Jiaming Yang 45 2 0 09 May 2024
Kermut: Composite kernel regression for protein variant effects Peter Mørch Groth Mads Herbert Kerrn Lars Olsen Jesper Salomon Wouter Boomsma 42 2 0 09 Apr 2024
Memory-Scalable and Simplified Functional Map Learning Robin Magnet M. Ovsjanikov 35 2 0 30 Mar 2024
Quantized Fourier and Polynomial Features for more Expressive Tensor Network Models Frederiek Wesel Kim Batselier 19 1 0 11 Sep 2023
Unbalanced Optimal Transport, from Theory to Numerics Thibault Séjourné Gabriel Peyré Franccois-Xavier Vialard OT 25 47 0 16 Nov 2022
Memory Safe Computations with XLA Compiler A. Artemev Tilman Roeder Mark van der Wilk 29 8 0 28 Jun 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
Learning Dynamical Systems via Koopman Operator Regression in Reproducing Kernel Hilbert Spaces Vladimir Kostic P. Novelli Andreas Maurer C. Ciliberto Lorenzo Rosasco Massimiliano Pontil 18 60 0 27 May 2022
Active Labeling: Streaming Stochastic Gradients Vivien A. Cabannes Francis R. Bach Vianney Perchet Alessandro Rudi 58 2 0 26 May 2022
Physics Informed Shallow Machine Learning for Wind Speed Prediction Daniele Lagomarsino Oneto Giacomo Meanti Nicolò Pagliana A. Verri A. Mazzino Lorenzo Rosasco A. Seminara 11 2 0 01 Apr 2022
Giga-scale Kernel Matrix Vector Multiplication on GPU Robert Hu Siu Lun Chau Dino Sejdinovic J. Glaunès 29 2 0 02 Feb 2022
Sublinear Time Approximation of Text Similarity Matrices Archan Ray Nicholas Monath Andrew McCallum Cameron Musco 32 7 0 17 Dec 2021
Sampling from Arbitrary Functions via PSD Models Ulysse Marteau-Ferey Francis R. Bach Alessandro Rudi 16 10 0 20 Oct 2021
Simple, Fast, and Flexible Framework for Matrix Completion with Infinite Width Neural Networks Adityanarayanan Radhakrishnan George Stefanakis M. Belkin Caroline Uhler 30 25 0 31 Jul 2021
Ada-BKB: Scalable Gaussian Process Optimization on Continuous Domains by Adaptive Discretization Marco Rando Luigi Carratino S. Villa Lorenzo Rosasco 41 5 0 16 Jun 2021
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients A. Artemev David R. Burt Mark van der Wilk 23 18 0 16 Feb 2021
Conditional Distributional Treatment Effect with Kernel Conditional Mean Embeddings and U-Statistic Regression Junhyung Park Uri Shalit Bernhard Schölkopf Krikamol Muandet CML 21 31 0 16 Feb 2021
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
A Framework for Interdomain and Multioutput Gaussian Processes Mark van der Wilk Vincent Dutordoir S. T. John A. Artemev Vincent Adam J. Hensman 40 94 0 02 Mar 2020
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 86 277 0 09 Aug 2012