Randomized Block Krylov Methods for Stronger and Faster Approximate
Singular Value Decomposition

v1v2v3v4 (latest)

Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

21 April 2015

Christopher Musco

ArXiv (abs)PDF HTML

Papers citing "Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition"

10 / 10 papers shown

Title
Range-Net: A High Precision Streaming SVD for Big Data Applications Gurpreet Singh Soumyajit Gupta Matthew Lease Clint Dawson 164 2 0 27 Oct 2020
Diffusion Approximations for Online Principal Component Estimation and Global Convergence C. J. Li Mengdi Wang Han Liu Tong Zhang 157 13 0 29 Aug 2018
Efficient Algorithms for Large-scale Generalized Eigenvector Computation and Canonical Correlation Analysis Rong Ge Chi Jin Sham Kakade Praneeth Netrapalli Aaron Sidford 275 82 0 13 Apr 2016
Near-Optimal Stochastic Approximation for Online Principal Component Estimation C. J. Li Mengdi Wang Han Liu Tong Zhang 293 68 0 16 Mar 2016
An Improved Gap-Dependency Analysis of the Noisy Power Method Maria-Florina Balcan S. Du Yining Wang Adams Wei Yu 206 75 0 23 Feb 2016
Low rank approximation and decomposition of large matrices using error correcting codes Shashanka Ubaru A. Mazumdar Y. Saad 112 11 0 30 Dec 2015
Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation Chi Jin Sham Kakade Cameron Musco Praneeth Netrapalli Aaron Sidford 162 43 0 29 Oct 2015
The Singular Value Decomposition, Applications and Beyond Zhihua Zhang 150 24 0 29 Oct 2015
Convergence of Stochastic Gradient Descent for PCA Ohad Shamir 191 87 0 30 Sep 2015
A Practical Guide to Randomized Matrix Computations with MATLAB Implementations Shusen Wang 306 41 0 28 May 2015