Co-Occuring Directions Sketching for Approximate Matrix Multiply
Machine Learning
2016-10-26 v1
Abstract
We introduce co-occurring directions sketching, a deterministic algorithm for approximate matrix product (AMM), in the streaming model. We show that co-occuring directions achieves a better error bound for AMM than other randomized and deterministic approaches for AMM. Co-occurring directions gives a -approximation of the optimal low rank approximation of a matrix product. Empirically our algorithm outperforms competing methods for AMM, for a small sketch size. We validate empirically our theoretical findings and algorithms
Cite
@article{arxiv.1610.07686,
title = {Co-Occuring Directions Sketching for Approximate Matrix Multiply},
author = {Youssef Mroueh and Etienne Marcheret and Vaibhava Goel},
journal= {arXiv preprint arXiv:1610.07686},
year = {2016}
}