Results 1 to 10 of about 1,040,614 (343)
Block Iterators for Sparse Matrices [PDF]
Annals of computer science and information systems, 2016 Finding an optimal block size for a given sparse matrix forms an important problem for storage formats that partition matrices into uniformly-sized blocks. Finding a solution to this problem can take a significant amount of time, which, effectively, may negate the benefits that such a format brings into sparse-matrix computations.
Daniel Langr +2 more
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Sparse Recovery Using Sparse Matrices [PDF]
Proceedings of the IEEE, 2009 In this paper, we survey algorithms for sparse recovery problems that are based on sparse random matrices. Such matrices has several attractive properties: they support algorithms with low computational complexity, and make it easy to perform incremental
Indyk, Piotr, Gilbert, Anna
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A note on the multiplication of sparse matrices
Open Computer Science, 2014 AbstractWe present a practical algorithm for multiplication of two sparse matrices. In fact if A and B are two matrices of size n with m 1 and m 2 non-zero elements respectively, then our algorithm performs O(min{m 1 n, m 2 n, m 1 m 2}) multiplications and O(k) additions where k is the number of non-zero elements in the tiny matrices that are obtained ...
Borna Keivan, Fard Sohrab
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Identification of Matrices Having a Sparse Representation [PDF]
IEEE Transactions on Signal Processing, 2008 We consider the problem of recovering a matrix from its action on a known vector in the setting where the matrix can be represented efficiently in a known matrix dictionary.
Pfander, Goetz E. +6 more
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Local Laws for Sparse Sample Covariance Matrices
Mathematics, 2022 We proved the local Marchenko–Pastur law for sparse sample covariance matrices that corresponded to rectangular observation matrices of order n×m with n/m→y (where y>0) and sparse probability npn>logβn (where β>0).
Alexander N. Tikhomirov +1 more
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The Electronic Journal of Linear Algebra, 2019 Given a polynomial $p(z)$, a companion matrix can be thought of as a simple template for placing the coefficients of $p(z)$ in a matrix such that the characteristic polynomial is $p(z)$.
Fischer, Jonathan +3 more
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Deterministic construction of sparse binary matrices via incremental integer optimization
Information Sciences, 2018 A central problem in compressed sensing (CS) is the design of measurement matrices. Compared with the conventional random matrices, sparse binary matrices have some attractive properties, such as lower storage/encoding cost and easy hardware ...
Zhu Liang Yu, Ling Cen, Zhenghui Gu
exaly +2 more sources
The Structure of Sparse Resultant Matrices
Proceedings of the 1997 international symposium on Symbolic and algebraic computation - ISSAC '97, 1997 Resultants characterize the existence of roots of systems of multivariate nonlinear polynomial equations, while their matrices reduce the computation of all common zeros to a problem in linear algebra.
Victor Y. Pan +2 more
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spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields
Journal of Statistical Software, 2010 spam is an R package for sparse matrix algebra with emphasis on a Cholesky factorization of sparse positive definite matrices. The implemantation of spam is based on the competing philosophical maxims to be competitively fast compared to existing tools ...
Reinhard Furrer, Stephan R. Sain
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Random matrices and random graphs* [PDF]
ESAIM: Proceedings and Surveys, 2023 We collect recent results on random matrices and random graphs. The topics covered are: fluctuations of the empirical measure of random matrices, finite-size effects of algorithms involving random matrices, characteristic polynomial of sparse matrices ...
Capitaine Mireille +4 more
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