Results 11 to 20 of about 739,476 (283)
Sparse Recovery Using Sparse Matrices [PDF]
Proceedings of the IEEE, 2010 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 updates to signals.
Piotr Indyk, Anna C Gilbert
exaly +5 more sources
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
doaj +3 more sources
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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Alternative methods for representing the inverse of linear programming basis matrices [PDF]
, 1988 Methods for representing the inverse of Linear Programming (LP) basis matrices are closely related to techniques for solving a system of sparse unsymmetric linear equations by direct methods.
Mitra, G, Tamiz, M
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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
doaj +1 more source
Subset Selection in Sparse Matrices [PDF]
SIAM Journal on Optimization, 2020 In subset selection we search for the best linear predictor that involves a small subset of variables. From a computational complexity viewpoint, subset selection is NP-hard and few classes are known to be solvable in polynomial time. Using mainly tools from discrete geometry, we show that some sparsity conditions on the original data matrix allow us ...
Alberto Del Pia +2 more
openaire +4 more sources
A program to reorder and solve sparse unsymmetric linear systems using the envelope method [PDF]
, 1987 The envelope data structure and the Choleski based (bordering) method for the solution of symmetric sparse systems of linear equations have been extended by the authors to solve unsymmetric systems of linear equations.
Mitra, G, Tamiz, M, Judice, JJ
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Sparse block-structured random matrices: universality
Journal of Physics: Complexity, 2023 We study ensembles of sparse block-structured random matrices generated from the adjacency matrix of a Erdös–Renyi random graph with N vertices of average degree Z , inserting a real symmetric d × d random block at each non-vanishing entry. We consider
Giovanni M Cicuta, Mario Pernici
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Adapting the interior point method for the solution of linear programs on high performance computers [PDF]
, 1991 In this paper we describe a unified algorithmic framework for the interior point method (IPM) of solving Linear Programs (LPs) which allows us to adapt it over a range of high performance computer architectures. We set out the reasons as to why IPM makes
Levkovitz, R, Mitra, G, Anderson, J
core +7 more sources
Nihon Kikai Gakkai ronbunshu, 2023 NV (Noise and Vibration) performance is determined by the influence of all components constituting a whole structure. It is difficult to design NV performance efficiently because the structural modification of a certain component affects the performance ...
Masashi INABA, Yuichi MATSUMURA
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