NeurIPS 2019poster23 citations
Decentralized sketching of low rank matrices
Rakshith Sharma Srinivasa, Kiryung Lee, Marius Junge, Justin Romberg
Abstract
We address a low-rank matrix recovery problem where each column of a rank-r matrix X of size (d1,d2) is compressed beyond the point of recovery to size L with L << d1. Leveraging the joint structure between the columns, we propose a method to recover the matrix to within an epsilon relative error in the Frobenius norm from a total of O(r(d
BibTeX
@inproceedings{NEURIPS2019_8dd291cb,
author = {Srinivasa, Rakshith Sharma and Lee, Kiryung and Junge, Marius and Romberg, Justin},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Decentralized sketching of low rank matrices},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/8dd291cbea8f231982db0fb1716dfc55-Paper.pdf},
volume = {32},
year = {2019}
}