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adj. spars·er, spars·est
Occurring, growing, or settled at widely spaced intervals; not thick or dense.

[Latin sparsus, past participle of spargere, to scatter.]

sparse′ly adv.
sparse′ness, spar′si·ty (spär′sĭ-tē) n.
American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.sparsity - the property of being scanty or scattered; lacking denseness
exiguity, leanness, meagerness, meagreness, scantiness, scantness, poorness - the quality of being meager; "an exiguity of cloth that would only allow of miniature capes"-George Eliot
Based on WordNet 3.0, Farlex clipart collection. © 2003-2012 Princeton University, Farlex Inc.
References in periodicals archive ?
(4) a routine to permute the columns of a sparse matrix and a routine to permute the rows of a full matrix.
In [9], the authors used the random sparse matrix as a new sparse measurement matrix and proposed an iterative algorithm of complexity of O(klog(k) log(n)), while it only required m = O(klog(n)) measurements.
The test matrices can be downloaded from the University of Florida Sparse Matrix Collection [14].
Comparing with Peng's method [16], our final projection matrix adds the sparse matrix [D.sub.1] and [D.sub.2].
L'([z.sub.k]) is a sparse matrix with nonzero elements [mathematical expression not reproducible].
SBM has characteristics of sparsity, binary, and incoherent, which is described as M x N sparse matrix with K as one of the elements in each column (K [much less than] M).
RPCA is a typical model utilizing the low-rank and sparse matrix decomposition for data restoration and denoising.
For instance, in the process of resolving second-kind integral equations via Wavelet-like technique, the whole discretized problem will be yielded to calculate the inverse of a large sparse matrix [27].
where Z stands for the original matrix needed to be restored, which is of low rank; E stands for outliers, which is a sparse matrix. Z and E need to be separated from the raw measurement matrix containing outliers [Z.sub.outlier] before generating attack vectors.
A regular grid of size 150 x 150 results in a sparse matrix of order n = 22500.