A Note on Element-wise Matrix Sparsification via a Matrix-valued Bernstein Inequality
Data Structures and Algorithms
2012-10-05 v2
Abstract
Given an n x n matrix A, we present a simple, element-wise sparsification algorithm that zeroes out all sufficiently small elements of A and then retains some of the remaining elements with probabilities proportional to the square of their magnitudes. We analyze the approximation accuracy of the proposed algorithm using a recent, elegant non-commutative Bernstein inequality, and compare our bounds with all existing (to the best of our knowledge) element-wise matrix sparsification algorithms.
Cite
@article{arxiv.1006.0407,
title = {A Note on Element-wise Matrix Sparsification via a Matrix-valued Bernstein Inequality},
author = {Petros Drineas and Anastasios Zouzias},
journal= {arXiv preprint arXiv:1006.0407},
year = {2012}
}
Comments
8 pages