Preconditioning Kernel Matrices

Preconditioning Kernel Matrices

22 February 2016

Michael A. Osborne

John P. Cunningham

Maurizio Filippone

Papers citing "Preconditioning Kernel Matrices"

15 / 15 papers shown

Title
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky Ethan N. Epperly J. Tropp R. Webber 30 3 0 04 Oct 2024
Gradients of Functions of Large Matrices Nicholas Krämer Pablo Moreno-Muñoz Hrittik Roy Søren Hauberg 32 0 0 27 May 2024
A Preconditioned Interior Point Method for Support Vector Machines Using an ANOVA-Decomposition and NFFT-Based Matrix-Vector Products Theresa Wagner John W. Pearson Martin Stoll 27 4 0 01 Dec 2023
Adaptive Cholesky Gaussian Processes Simon Bartels Kristoffer Stensbo-Smidt Pablo Moreno-Muñoz Wouter Boomsma J. Frellsen Søren Hauberg 22 3 0 22 Feb 2022
When are Iterative Gaussian Processes Reliably Accurate? Wesley J. Maddox Sanyam Kapoor A. Wilson 13 10 0 31 Dec 2021
Incremental Ensemble Gaussian Processes Qin Lu G. V. Karanikolas G. Giannakis 40 23 0 13 Oct 2021
Preconditioning for Scalable Gaussian Process Hyperparameter Optimization Jonathan Wenger Geoff Pleiss Philipp Hennig John P. Cunningham J. Gardner 12 23 0 01 Jul 2021
Hierarchical Inducing Point Gaussian Process for Inter-domain Observations Luhuan Wu Andrew C. Miller Lauren Anderson Geoff Pleiss David M. Blei John P. Cunningham 15 8 0 28 Feb 2021
Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients A. Artemev David R. Burt Mark van der Wilk 16 18 0 16 Feb 2021
Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization Geoff Pleiss M. Jankowiak David Eriksson Anil Damle J. Gardner 17 43 0 19 Jun 2020
Scaling Gaussian Process Regression with Derivatives David Eriksson Kun Dong E. Lee D. Bindel A. Wilson GP 14 75 0 29 Oct 2018
Bayesian Inference of Log Determinants Jack K. Fitzsimons Kurt Cutajar Michael A. Osborne Stephen J. Roberts Maurizio Filippone 26 18 0 05 Apr 2017
Diving into the shallows: a computational perspective on large-scale shallow learning Siyuan Ma M. Belkin 16 75 0 30 Mar 2017
Faster Kernel Ridge Regression Using Sketching and Preconditioning H. Avron K. Clarkson David P. Woodruff 25 121 0 10 Nov 2016
A Framework for Evaluating Approximation Methods for Gaussian Process Regression Krzysztof Chalupka Christopher K. I. Williams Iain Murray GP 71 169 0 29 May 2012