Results 41 to 50 of about 1,040,614 (343)
Efficient Frequent Directions Algorithm for Sparse Matrices [PDF]
Knowledge Discovery and Data Mining, 2016 This paper describes Sparse Frequent Directions, a variant of Frequent Directions for sketching sparse matrices. It resembles the original algorithm in many ways: both receive the rows of an input matrix An x d one by one in the streaming setting and ...
Mina Ghashami +2 more
semanticscholar +1 more source
Journal of Telecommunications and Information Technology, 2019 This paper considers several algorithms for parallelizing the procedure of forward and back substitution for high-order symmetric sparse matrices on multi-core computers with shared memory.
Sergiy Fialko
doaj +1 more source
An efficient sparse regularity concept [PDF]
, 2009 Let A be a 0/1 matrix of size m×n, and let p be the density of A (i.e., the number of ones divided by m · n). We show that A can be approximated in the cut norm within ε · mnp by a sum of cut matrices (of rank 1), where the number of summands is ...
Cooper, Colin +8 more
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Sparse Matrix Based Low-Complexity, Recursive, and Radix-2 Algorithms for Discrete Sine Transforms
IEEE Access, 2021 This paper presents factorizations of each discrete sine transform (DST) matrix of types I, II, III, and IV into a product of sparse, diagonal, bidiagonal, and scaled orthogonal matrices.
Sirani M. Perera, Levi E. Lingsch
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New Directions In Sparse Sampling and Estimation For Underdetermined Systems [PDF]
, 2013 A central objective in signal processing is to infer meaningful information from a set of measurements or data. While most signal models have an overdetermined structure (the number of unknowns less than the number of equations), traditionally very few ...
Piya Pal, Pal, Piya
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Outliers in spectrum of sparse Wigner matrices [PDF]
Random Struct. Algorithms, 2019 In this paper, we study the effect of sparsity on the appearance of outliers in the semi‐circular law. Let (Wn)n=1∞ be a sequence of random symmetric matrices such that each Wn is n × n with i.i.d.
K. Tikhomirov, Pierre Youssef
semanticscholar +1 more source
Fast Hierarchical Solvers For Sparse Matrices Using Extended Sparsification and Low-Rank Approximation [PDF]
SIAM Journal on Scientific Computing, 2015 Sparse linear systems are ubiquitous in various scientific computing applications. Inversion of sparse matrices with standard direct solve schemes are prohibitive for large systems due to their quadratic/cubic complexity.
H. Pouransari, P. Coulier, Eric F Darve
semanticscholar +1 more source
Insights from classifying visual concepts with multiple kernel learning. [PDF]
PLoS ONE, 2012 Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL)
Alexander Binder +7 more
doaj +1 more source
On large-scale diagonalization techniques for the Anderson model of localization [PDF]
, 2006 We propose efficient preconditioning algorithms for an eigenvalue problem arising in quantum physics, namely the computation of a few interior eigenvalues and their associated eigenvectors for large-scale sparse real and symmetric indefinite matrices of ...
Bollhofer, Matthias +8 more
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Lower bounds for sparse matrix vector multiplication on hypercubic networks [PDF]
Discrete Mathematics & Theoretical Computer Science, 1998 In this paper we consider the problem of computing on a local memory machine the product y = Ax,where A is a random n×n sparse matrix with Θ(n) nonzero elements.
Giovanni Manzini
doaj +2 more sources