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A new research paper titled “Discovering faster matrix multiplication algorithms with reinforcement learning” was published by researchers at DeepMind. “Here we report a deep reinforcement learning ...
Matrix multiplication is at the heart of many machine learning breakthroughs, and it just got faster—twice. Last week, DeepMind announced it discovered a more efficient way to perform matrix ...
Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special ...
This is a preview. Log in through your library . Abstract The sparsity constrained rank-one matrix approximation problem is a difficult mathematical optimization problem which arises in a wide array ...
Abstract. In this paper, an iterative method is presented to solve the linear matrix equation AXB = C over the generalized reflexive (or anti-reflexive) matrix X (A ∈ Rp×n; B ∈ Rm×q, C ∈ Rp×q, X ∈ ...
SAN FRANCISCO--(BUSINESS WIRE)--Dividend Finance, LLC (“Dividend” or the “Company”) has partnered with Digital Matrix Systems, Inc. (“DMS”) to turbo-charge its capabilities in deploying customizable ...
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