作者: Etienne Marcheret , Vaibhava Goel , Youssef Mroueh
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摘要: We introduce co-occurring directions sketching, a deterministic algorithm for approximate matrix product (AMM), in the streaming model. show that co-occuring achieves better error bound AMM than other randomized and approaches AMM. Co-occurring gives $1 + \epsilon$ -approximation of optimal low rank approximation product. Empirically our outperforms competing methods AMM, small sketch size. validate empirically theoretical findings algorithms