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Volumn , Issue , 2014, Pages

Generalised Scalable Robust principal component analysis

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; RELAXATION PROCESSES; ROBUST CONTROL;

EID: 85088195365     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/c.28.116     Document Type: Conference Paper
Times cited : (9)

References (17)
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    • Bao, B.-K.1    Liu, G.2    Xu, C.3    Yan, S.4
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  • 5
    • 84877790369 scopus 로고    scopus 로고
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    • D. Chen and L.-Z. Cheng. Image inpainting based on low-rank and joint-sparse matrix recovery. Electronics Letters, 49(1):35-36, 2013.
    • (2013) Electronics Letters , vol.49 , Issue.1 , pp. 35-36
    • Chen, D.1    Cheng, L.-Z.2
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    • 33744552752 scopus 로고    scopus 로고
    • For most large underdetermined systems of equations, the minimal ℓ1- norm near-solution approximates the sparsest near-solution
    • D. Donoho. For most large underdetermined systems of equations, the minimal ℓ1- norm near-solution approximates the sparsest near-solution. Communications on Pure and Applied Mathematics, 59(7):907-934, 2006.
    • (2006) Communications on Pure and Applied Mathematics , vol.59 , Issue.7 , pp. 907-934
    • Donoho, D.1
  • 7
    • 0142257025 scopus 로고    scopus 로고
    • PhD thesis, Dept. Electrical Engineering, Stanford University, CA, USA
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    • (2002) Matrix Rank Minimization with Applications
    • Fazel, M.1
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    • Hotelling, H.1
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    • 0004262735 scopus 로고
    • J. Wiley, and W. InterScience Wiley New York
    • P.J. Huber, J. Wiley, and W. InterScience. Robust statistics. Wiley New York, 1981.
    • (1981) Robust Statistics
    • Huber, P.J.1
  • 13
    • 84874199238 scopus 로고    scopus 로고
    • Active subspace: Toward scalable low-rank learning
    • G. Liu and S. Yan. Active subspace: Toward scalable low-rank learning. Neural Comput., 24(12):3371-3394, 2012.
    • (2012) Neural Comput. , vol.24 , Issue.12 , pp. 3371-3394
    • Liu, G.1    Yan, S.2
  • 14
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    • Joint schatten p-norm and ℓp-norm robust matrix completion for missing value recovery
    • F. Nie, H. Wang, H. Huang, and Ch. Ding. Joint schatten p-norm and ℓp-norm robust matrix completion for missing value recovery. Knowledge and Information Systems, pages 1-20, 2013.
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    • Toward a practical face recognition system: Robust alignment and illumination by sparse representation
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    • Visual saliency detection via sparsity pursuit
    • J. Yan, M. Zhu, H. Liu, and Y. Liu. Visual saliency detection via sparsity pursuit. IEEE Signal Processing Letters, 17(8):739-742, 2010.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.