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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
Minimum Error Bounded Efficient L1 Tracker with Occlusion Detection (PREPRINT)
Abstract : Recently, sparse representation has been applied to visual tracking to find the target with the minimum reconstruction… 
Highly Cited
2010
Highly Cited
2010
Optimum Subspace Learning and Error Correction for Tensors
Confronted with the high-dimensional tensor-like visual data, we derive a method for the decomposition of an observed tensor into… 
Highly Cited
2007
Highly Cited
2007
Deformable Template As Active Basis
This article proposes an active basis model and a shared pursuit algorithm for learning deformable templates from image patches… 
Highly Cited
2006
Highly Cited
2006
Obstacle Avoidance For Unmanned Air Vehicles Using Image Feature Tracking
This paper discusses a computer vision algorithm and a control law for obstacle avoidance for small unmanned air vehicles using a… 
Highly Cited
2005
Highly Cited
2005
Novel pixel architecture with inherent background suppression for 3D time-of-flight imaging
The time-of-flight (TOF) principle is a well known principle to acquire a scene in all three dimensions. The advantages of the… 
Highly Cited
2000
Highly Cited
2000
FRAME DESIGN USING FOCUSS WITH METHOD OF OPTIMAL DIRECTIONS (MOD)
The equation b = Ax + n where the columns of A form an overcomplete set, i.e. the system is underdetermined, and with a sparsity… 
Highly Cited
1995
Highly Cited
1995
Speaker recognition using hidden Markov models, dynamic time warping and vector quantisation
The authors evaluate continuous density hidden Markov models (CDHMM), dynamic time warping (DTW) and distortion-based vector… 
Highly Cited
1990
Highly Cited
1990
Poor Estimates of Context are Worse than None
It is difficult to estimate the probability of a word's context because of sparse data problems. If appropriate care is taken, we… 
Highly Cited
1986
Highly Cited
1986
Direct methods for sparse matrices27100
Highly Cited
1983
Highly Cited
1983
Iterative algorithms for large sparse linear systems on parallel computers
Large sparse linear systems of equations require hours to solve on conventional mainframe computers: however, with the advent of… 
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