This paper presents a numerical comparison between algorithms for unconstrained optimization that take account of sparsity in the second derivative matrix of the objective function. Some of the ...
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 ...
Texas A&M professor to highlight how mathematics connects algorithms, art, and music in a free public lecture on July 30. Philadelphia, PA, July 22, 2025 (GLOBE NEWSWIRE) -- Mathematics and code are ...
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 ...
New York, October 4, 2023 – ACM, the Association for Computing Machinery, and IEEE Computer Society have named Keshav Pingali, the W.A.”Tex” Moncrief Chair of Grid and Distributed Computing at the ...
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