sparse

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sparse

A sparse matrix (or vector, or array) is one in which most of the elements are zero. If storage space is more important than access speed, it may be preferable to store a sparse matrix as a list of (index, value) pairs or use some kind of hash scheme or associative memory.
References in periodicals archive ?
It is also possible to compute gradients (a special case of Jacobians) of structured computations by exposing the sparsity in an associated extended Jacobian matrix [Coleman and Jonsson 1999].
Intelligent Sparse Reporting: Exclusive to the ShowCase offering, Intelligent Sparse Reporting is designed to speed up response time and optimize system resource usage in Essbase databases that contain a high degree of sparsity.
Representative Nygren and Senator Marklein are authoring legislation (Assembly Bill 835 / Senate Bill 690) that increases Sparsity Aid by $6.
complement a user's rating profile by merging those of trusted users through which better recommendations can be fabricate and the cold start and data sparsity harms can be better handled.
where [beta] is the weight of the sparsity penalty term and KL ([rho] [parallel] [[?
Recently, [14] proposes a parts-based method (latent spaces with structured sparsity, LSSS) based on SSPCA, where the optimization is elegantly converted to two convex optimization problems.
But there is concern about plans to pay schools on a per pupil basis with the total amount calculated based on 11 different factors such as low prior attainment, deprivation and sparsity.
UniServer brings together experts from the world's leading processor, server-on-chip and software development industry ARM, Applied-Micro and IBM as well as emerging application developers Worldsensing, Sparsity and Meritorius.
According to this figure, the algorithm collects likelihood values according to the requirements of the optimal seed model in 8 different kinds of network sparsity scales and when the Markor link tends to be steady.
He added: "The Government must address the funding issues associated with sparsity within the local Government funding model so Northumberland is not disadvantaged.
p] is a quantitative index to measure the sparsity of a signal.
One feasible way to learn such a graphical model is to capture any conditional independence between each pair of the variables with a sparsity prior.