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Sparse approximation

Known as: Sparse optimization, Sparse representation 
A sparse approximation is a sparse vector that approximately solves a system of equations. Techniques for finding sparse approximations have found… 
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Related topics

Related topics

24 relations
Ali AkansuBasis pursuitBasis pursuit denoisingCombinatorial optimization

Broader (1)

Numerical linear algebra

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2018
Highly Cited
2018
Robust, discriminative and comprehensive dictionary learning for face recognition
Highly Cited
2016
Highly Cited
2016
Hyperspectral Image Classification by Fusing Collaborative and Sparse Representations
This paper proposes to combine collaborative representation (CR) and sparse representation (SR) for hyperspectral image… 
Highly Cited
2014
Highly Cited
2014
Learning sparse dictionaries for music and speech classification
The field of music and speech classification is quite mature with researchers having settled on the approximate best… 
Highly Cited
2013
Highly Cited
2013
Single-Sample Face Recognition with Image Corruption and Misalignment via Sparse Illumination Transfer
Single-sample face recognition is one of the most challenging problems in face recognition. We propose a novel face recognition… 
Highly Cited
2012
Highly Cited
2012
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target… 
2011
2011
Speaker Verification Using Sparse Representations on Total Variability i-vectors
In this paper, the sparse representation computed by lminimization with quadratic constraints is employed to model the i-vectors… 
Highly Cited
2010
Highly Cited
2010
Local Sparse Representation Based Classification
In this paper, we address the computational complexity issue in Sparse Representation based Classification (SRC). In SRC, it is… 
Highly Cited
2006
Highly Cited
2006
MR Image Reconstruction from Sparse Radial Samples Using Bregman Iteration
2 1 || ) ( || || ) ( || || || L k L BV v y f NFFT f f − − + Ψ + λ υ , where vk=y+ vk-1-NFFT(fk) with the convention v0=0, to… 
Highly Cited
1999
Highly Cited
1999
Solving Hyperbolic PDEs Using Interpolating Wavelets
A method is presented for adaptively solving hyperbolic PDEs. The method is based on an interpolating wavelet transform using… 
1992
1992
Sparse Approximation for Solving Integral Equations with Oscillatory Kernels
An integral equation formulation of Helmholtz’s equation is considered as an example of a problem with an oscillatory kernel. For… 
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