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Fast computation of low rank matrix approximations
D. Achlioptas and F. McSherry · 2001
Earlier work this paper cites.
Fast computation of low-rank matrix approximations
D. Achlioptas and F. McSherry · 2007
Earlier work this paper cites.

Similar

A note on element-wise matrix sparsification via a matrix-valued Bernstein inequality
P. Drineas and A. Zouzias · 2011
Cited alongside, same era.
A simpler approach to matrix completion
B. Recht · 2011
Cited alongside, same era.

Then

Matrix entry-wise sampling: Simple is best
D. Achlioptas, Z. Karnin, and E. Liberty · 2013
Later among the works it cites.

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2014

A Note on Randomized Element-wise Matrix Sparsification

Kundu, Abhisek, Drineas, Petros

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Given a matrix A \in R^{m x n}, we present a randomized algorithm that sparsifies A by retaining some of its elements by sampling them according to a distribution that depends on both the square and the absolute value of the entries.

We combine the ideas of [4, 1] and provide an elementary proof of the approximation accuracy of our algorithm following [4] without the truncation step.