Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices

11 April 2017

Papers citing "Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices"

12 / 12 papers shown

Title
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky Ethan N. Epperly J. Tropp R. Webber 34 3 0 04 Oct 2024
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning Michal Dereziñski Christopher Musco Jiaming Yang 48 2 0 09 May 2024
Relating tSNE and UMAP to Classical Dimensionality Reduction Andrew Draganov Simon Dohn FAtt 27 4 0 20 Jun 2023
Krylov Methods are (nearly) Optimal for Low-Rank Approximation Ainesh Bakshi Shyam Narayanan 31 6 0 06 Apr 2023
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation Ainesh Bakshi Piotr Indyk Praneeth Kacham Sandeep Silwal Samson Zhou 38 4 0 01 Dec 2022
Sublinear Time Approximation of Text Similarity Matrices Archan Ray Nicholas Monath Andrew McCallum Cameron Musco 32 7 0 17 Dec 2021
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra Nadiia Chepurko K. Clarkson L. Horesh Honghao Lin David P. Woodruff 24 24 0 09 Nov 2020
Generalized Leverage Score Sampling for Neural Networks J. Lee Ruoqi Shen Zhao Song Mengdi Wang Zheng Yu 21 42 0 21 Sep 2020
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation H. Diao Rajesh Jayaram Zhao Song Wen Sun David P. Woodruff 19 43 0 29 Sep 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$ -means Clustering Manuel Fernández David P. Woodruff T. Yasuda 29 6 0 15 May 2019
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? Cameron Musco David P. Woodruff 31 13 0 05 Nov 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data J. Tropp A. Yurtsever Madeleine Udell V. Cevher 23 80 0 18 Jun 2017