Co-Occuring Directions Sketching for Approximate Matrix Multiply

October 25, 2016 ยท Declared Dead ยท ๐Ÿ› International Conference on Artificial Intelligence and Statistics

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Authors Youssef Mroueh, Etienne Marcheret, Vaibhava Goel arXiv ID 1610.07686 Category cs.LG: Machine Learning Citations 9 Venue International Conference on Artificial Intelligence and Statistics Last Checked 6 months ago
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 $1 + ฮต$ -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
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