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Sparse matrix

Known as: Dense matrix, Sparse vector, Sparsity 
In numerical analysis, a sparse matrix is a matrix in which most of the elements are zero. By contrast, if most of the elements are nonzero, then the… 
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APMonitorARPACKASCENDASTAP

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2011
Highly Cited
2011
GoDec: Randomized Lowrank & Sparse Matrix Decomposition in Noisy Case
Low-rank and sparse structures have been profoundly studied in matrix completion and compressed sensing. In this paper, we… 
Highly Cited
2009
Highly Cited
2009
Rank-Sparsity Incoherence for Matrix Decomposition
Suppose we are given a matrix that is formed by adding an unknown sparse matrix to an unknown low-rank matrix. Our goal is to… 
Highly Cited
2009
Highly Cited
2009
Parallel sparse matrix-vector and matrix-transpose-vector multiplication using compressed sparse blocks
This paper introduces a storage format for sparse matrices, called <b><i>compressed sparse blocks (CSB)</i></b>, which allows… 
Highly Cited
2009
Highly Cited
2009
Sparse subspace clustering
We propose a method based on sparse representation (SR) to cluster data drawn from multiple low-dimensional linear or affine… 
Highly Cited
2007
Highly Cited
2007
Optimization of sparse matrix-vector multiplication on emerging multicore platforms
We are witnessing a dramatic change in computer architecture due to the multicore paradigm shift, as every electronic device from… 
Highly Cited
2007
Highly Cited
2007
Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria
An unsupervised learning algorithm for the separation of sound sources in one-channel music signals is presented. The algorithm… 
Highly Cited
2004
Highly Cited
2004
Sparsity: Optimization Framework for Sparse Matrix Kernels
Sparse matrix–vector multiplication is an important computational kernel that performs poorly on most modern processors due to a… 
Highly Cited
2003
Highly Cited
2003
Automatic performance tuning of sparse matrix kernels
This dissertation presents an automated system to generate highly efficient, platform-adapted implementations of sparse matrix… 
Highly Cited
1999
Highly Cited
1999
Hypergraph-Partitioning-Based Decomposition for Parallel Sparse-Matrix Vector Multiplication
In this work, we show that the standard graph-partitioning-based decomposition of sparse matrices does not reflect the actual… 
Highly Cited
1990
Highly Cited
1990
A Basic Tool Kit for Sparse Matrix Computations
Presented here are the main features of a tool package for manipulating and working with sparse matrices. One of the goals of the… 
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