Sparse matrix computations are pivotal to advancing high-performance scientific applications, particularly as modern numerical simulations and data analyses demand efficient management of large, ...
A novel AI-acceleration paper presents a method to optimize sparse matrix multiplication for machine learning models, particularly focusing on structured sparsity. Structured sparsity involves a ...
This article demonstrates a fast and practical procedure for the maximum likelihood estimation of models with spatial interaction on a lattice, such as Gaussian Markov random fields (conditional ...
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