Journal of the Royal Statistical Society. Series B (Statistical Methodology), Vol. 79, No. 5 (NOVEMBER 2017), pp. 1295-1366 (72 pages) Statistical network modelling has focused on representing the ...
Sparse matrix computations are prevalent in many scientific and technical applications. In many simulation applications, the solving of the sparse matrix-vector multiplication (SpMV) is critical for ...
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 ...
We consider inhomogeneous Erdős–Rényi graphs. We suppose that the maximal mean degree d satisfies d ≪ logn. We characterise the asymptotic behaviour of the n1–o(1) largest eigenvalues of the adjacency ...
I'm getting ready to start working on a C/C++ project that will be building and solving large tri-diagonal, block tri-diagonal and triangular matrices. I know there are a lot of libraries available ...
The classic sparse matrix screen based on Jancaric and Kim (1991) and modified by Cudney et al (1994). Samples salts, polymers, organics and pH (see conditions). Helsinki Random II A combined sparse ...
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