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Volumn 5, Issue , 2014, Pages 4108-4117

Structured low-rank matrix factorization: Optimality, algorithm, and applications to image processing

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; FACTORIZATION; IMAGE PROCESSING; LEARNING SYSTEMS; OPTIMIZATION;

EID: 84919830640     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (60)

References (21)
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    • Beck, A.1    Teboulle, M.2
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    • A unifying approach to isotropic and anisotropic total variation denoising models
    • Birkholz, H. A unifying approach to isotropic and anisotropic total variation denoising models. J. of Computational and Applied Mathematics, 235:2502-2514, 2011.
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    • Birkholz, H.1
  • 7
    • 21644465788 scopus 로고    scopus 로고
    • Local minima and convergence in low-rank semidenite programming
    • Burer, S. and Monteiro, R. D. C. Local minima and convergence in low-rank semidenite programming. Mathematical Programming, Series A, (103):427-444, 2005.
    • (2005) Mathematical Programming, Series A , vol.103 , pp. 427-444
    • Burer, S.1    Monteiro, R.D.C.2
  • 12
    • 78549288866 scopus 로고    scopus 로고
    • Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
    • Recht, B., Fazel, M., and Parrilo, P. A. Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Review, 52:471-501, 2010.
    • (2010) SIAM Review , vol.52 , pp. 471-501
    • Recht, B.1    Fazel, M.2    Parrilo, P.A.3
  • 14
    • 84907737173 scopus 로고    scopus 로고
    • Compressive sensing by random convolution
    • November
    • Romberg, J. Compressive sensing by random convolution. SIAM J. Img. Sei., 2(4): 1098-1128, November 2009. ISSN 1936-4954.
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    • Romberg, J.1
  • 15
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    • Nonlinear total variation based noise removal algorithms
    • Rudin, L. I., Osher, S., and Fatemi, E. Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena, 60:259-268, 1992.
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    • Rudin, L.I.1    Osher, S.2    Fatemi, E.3
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    • Pyramidal neurons: Dendritic structure and synaptic integration
    • Spruston, N. Pyramidal neurons: Dendritic structure and synaptic integration. Nature Reviews Neuroscience, 9: 206-221,2008.
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    • Spruston, N.1
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    • 84885030988 scopus 로고    scopus 로고
    • A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion
    • Xu, Y. and Yin, W. A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion. SIAM Journal of Imaging Sciences, 6(3): 1758-1789, 2013.
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    • Xu, Y.1    Yin, W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.