Arbitrary Block-Sparse Signal Reconstruction Based on Incomplete Single Measurement Vector
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0528-3
Abstract: Within the compressive sensing framework, reconstruction algorithms of block-sparse signal (BSS) often have special requirements on sparsity patterns. As a result, only some particular BSSs can be reconstructed. In this paper, we present a new… read more here.
Keywords: reconstruction; block; sparse signal; sparsity ... See more keywords
Orthogonal Matched Wavelets with Vanishing Moments: A Sparsity Design Approach
Sign Up to like & getrecommendations! Published in 2018 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-017-0716-1
Abstract: This paper presents a novel approach to design orthogonal wavelets matched to a signal with compact support and vanishing moments. It provides a systematic and versatile framework for matching an orthogonal wavelet to a specific… read more here.
Keywords: orthogonal matched; vanishing moments; approach; wavelet ... See more keywords
MOEA/D with chain-based random local search for sparse optimization
Sign Up to like & getrecommendations! Published in 2018 at "Soft Computing"
DOI: 10.1007/s00500-018-3460-y
Abstract: The goal in sparse approximation is to find a sparse representation of a system. This can be done by minimizing a data-fitting term and a sparsity term at the same time. This sparse term imposes… read more here.
Keywords: moea; chain based; sparse; sparse optimization ... See more keywords
Exploiting label consistency in structured sparse representation for classification
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3479-0
Abstract: Sparse representation with adaptive dictionaries has emerged as a promising tool in computer vision and pattern analysis. While standard sparsity promoted by $$\ell _0$$ℓ0 or $$\ell _1$$ℓ1 regularization has been widely used, recent approaches seek… read more here.
Keywords: consistency; sparse representation; sparsity; label consistency ... See more keywords
Feature selection with MCP$$^2$$2 regularization
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3500-7
Abstract: Feature selection, as a fundamental component of building robust models, plays an important role in many machine learning and data mining tasks. Recently, with the development of sparsity research, both theoretical and empirical studies have… read more here.
Keywords: selection mcp; feature selection; non convex; regularization ... See more keywords
Exploiting Sparsity for Semi-Algebraic Set Volume Computation
Sign Up to like & getrecommendations! Published in 2022 at "Foundations of Computational Mathematics"
DOI: 10.1007/s10208-021-09508-w
Abstract: We provide a systematic deterministic numerical scheme to approximate the volume (i.e., the Lebesgue measure) of a basic semi-algebraic set whose description follows a correlative sparsity pattern. As in previous works (without sparsity), the underlying… read more here.
Keywords: volume; exploiting sparsity; semi algebraic; sparsity ... See more keywords
Weighted thresholding homotopy method for sparsity constrained optimization
Sign Up to like & getrecommendations! Published in 2020 at "Journal of Combinatorial Optimization"
DOI: 10.1007/s10878-020-00563-7
Abstract: We propose in this paper a novel weighted thresholding method for the sparsity-constrained optimization problem. By reformulating the problem equivalently as a mixed-integer programming, we investigate the Lagrange duality with respect to an $$l_1$$ l… read more here.
Keywords: method; weighted thresholding; optimization; constrained optimization ... See more keywords
An Approach to Alleviate the Sparsity Problem of Hybrid Collaborative Filtering Based Recommendations: The Product-Attribute Perspective from User Reviews
Sign Up to like & getrecommendations! Published in 2020 at "Mobile Networks and Applications"
DOI: 10.1007/s11036-019-01246-2
Abstract: The goal of a recommender system is to return related items that users may be interested in. However recommendation methods result in a sparsity problem that affects the generation of recommendation results and, thus, the… read more here.
Keywords: sparsity problem; product attribute; product; recommendation ... See more keywords
Superpixel guided structure sparsity for multispectral and hyperspectral image fusion over couple dictionary
Sign Up to like & getrecommendations! Published in 2019 at "Multimedia Tools and Applications"
DOI: 10.1007/s11042-019-7188-1
Abstract: This paper proposed a hyperspectral (HS) and multispectral (MS) image fusion method based on superpixel guided structure sparsity and couple dictionary (SGSSCD). It is assumed that the pixels in a homogeneous area of MS image… read more here.
Keywords: resolution; image; couple dictionary; sparsity ... See more keywords
Sparsity-based no-reference image quality assessment for automatic denoising
Sign Up to like & getrecommendations! Published in 2018 at "Signal, Image and Video Processing"
DOI: 10.1007/s11760-017-1215-3
Abstract: In image and video denoising, a quantitative measure of genuine image content, noise, and blur is required to facilitate quality assessment, when the ground truth is not available. In this paper, we present a no-reference… read more here.
Keywords: quality; image; quality assessment; reference image ... See more keywords
Neuronal competition: microcircuit mechanisms define the sparsity of the engram
Sign Up to like & getrecommendations! Published in 2019 at "Current Opinion in Neurobiology"
DOI: 10.1016/j.conb.2018.10.013
Abstract: Extensive work in computational modeling has highlighted the advantages for employing sparse yet distributed data representation and storage Kanerva (1998), properties that extend to neuronal networks encoding mnemonic information (memory traces or engrams). While neurons… read more here.
Keywords: competition microcircuit; sparsity engram; microcircuit mechanisms; sparsity ... See more keywords