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Volumn 2, Issue January, 2014, Pages 1350-1358

Efficient structured matrix rank minimization

Author keywords

[No Author keywords available]

Indexed keywords

COMPRESSED SENSING; CONSTRAINED OPTIMIZATION; GRADIENT METHODS; INFORMATION SCIENCE; ITERATIVE METHODS; LINEAR SYSTEMS; OPTIMIZATION; STOCHASTIC SYSTEMS;

EID: 84937904469     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (20)

References (29)
  • 1
    • 84877776210 scopus 로고    scopus 로고
    • Spectral learning of general weighted automata via constrained matrix completion
    • B. Balle and M. Mohri. Spectral learning of general weighted automata via constrained matrix completion. In NIPS, pages 2168-2176, 2012.
    • (2012) NIPS , pp. 2168-2176
    • Balle, B.1    Mohri, M.2
  • 2
    • 85014561619 scopus 로고    scopus 로고
    • A fast iterative shrinkage-thresholding algorithm for linear inverse problems
    • A. Beck and M. Teboulle. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sciences, 2(1): 183-202, 2009.
    • (2009) SIAM J. Imaging Sciences , vol.2 , Issue.1 , pp. 183-202
    • Beck, A.1    Teboulle, M.2
  • 3
    • 58849152261 scopus 로고    scopus 로고
    • A generalized conditional gradient method and its connection to an iterative shrinkage method
    • K. Bredies, D. A. Lorenz, and P. Maass. A generalized conditional gradient method and its connection to an iterative shrinkage method. Computational Optimization and Applications, 42(2): 173-193, 2009.
    • (2009) Computational Optimization and Applications , vol.42 , Issue.2 , pp. 173-193
    • Bredies, K.1    Lorenz, D.A.2    Maass, P.3
  • 5
    • 77951528523 scopus 로고    scopus 로고
    • The power of convex relaxation: Near-optimal matrix completion
    • E. J. Candès and T. Tao. The power of convex relaxation: near-optimal matrix completion. IEEE Transactions on Information Theory, 56(5): 2053-2080, 2010.
    • (2010) IEEE Transactions on Information Theory , vol.56 , Issue.5 , pp. 2053-2080
    • Candès, E.J.1    Tao, T.2
  • 6
    • 84895538549 scopus 로고    scopus 로고
    • Spectral compressed sensing via structured matrix completion
    • Y. Chen and Y. Chi. Spectral compressed sensing via structured matrix completion. In ICML, pages 414-422, 2013.
    • (2013) ICML , pp. 414-422
    • Chen, Y.1    Chi, Y.2
  • 8
    • 50649094197 scopus 로고    scopus 로고
    • A rank minimization approach to video inpainting
    • T. Ding, M. Sznaier, and O. I. Camps. A rank minimization approach to video inpainting. In ICCV, pages 1-8, 2007.
    • (2007) ICCV , pp. 1-8
    • Ding, T.1    Sznaier, M.2    Camps, O.I.3
  • 11
    • 84887350278 scopus 로고    scopus 로고
    • Hankel matrix rank minimization with applications to system identification and realization
    • M. Fazel, T. K. Pong, D. Sun, and P. Tseng. Hankel matrix rank minimization with applications to system identification and realization. SIAM J. Matrix Analysis Applications, 34(3): 946-977, 2013.
    • (2013) SIAM J. Matrix Analysis Applications , vol.34 , Issue.3 , pp. 946-977
    • Fazel, M.1    Pong, T.K.2    Sun, D.3    Tseng, P.4
  • 14
    • 0026922942 scopus 로고
    • Estimating two-dimensional frequencies by matrix enhancement and matrix pencil
    • Y. Hua. Estimating two-dimensional frequencies by matrix enhancement and matrix pencil. IEEE Transactions on Signal Processing, 40(9): 2267-2280, 1992.
    • (1992) IEEE Transactions on Signal Processing , vol.40 , Issue.9 , pp. 2267-2280
    • Hua, Y.1
  • 15
    • 84907818530 scopus 로고    scopus 로고
    • Factorization approach to structured low-rank approximation with applications
    • M. Ishteva, K. Usevich, and I. Markovsky. Factorization approach to structured low-rank approximation with applications. SIAM J. Matrix Analysis Applcations, 35(3): 1180-1204, 2014.
    • (2014) SIAM J. Matrix Analysis Applcations , vol.35 , Issue.3 , pp. 1180-1204
    • Ishteva, M.1    Usevich, K.2    Markovsky, I.3
  • 16
    • 84897524603 scopus 로고    scopus 로고
    • Revisiting frank-wolfe: Projection-free sparse convex optimization
    • M. Jaggi. Revisiting Frank-Wolfe: Projection-free sparse convex optimization. In ICML, pages 427-435, 2013.
    • (2013) ICML , pp. 427-435
    • Jaggi, M.1
  • 17
    • 77950841024 scopus 로고    scopus 로고
    • Semidefinite programming methods for system realization and identification
    • Z. Liu and L. Vandenberghe. Semidefinite programming methods for system realization and identification. In CDC, pages 4676-4681, 2009.
    • (2009) CDC , pp. 4676-4681
    • Liu, Z.1    Vandenberghe, L.2
  • 18
    • 72549110327 scopus 로고    scopus 로고
    • Interior-point method for nuclear norm approximation with application to system identification
    • Z. Liu and L. Vandenberghe. Interior-point method for nuclear norm approximation with application to system identification. SIAM J. Matrix Analysis Applications, 31(3): 1235-1256, 2009.
    • (2009) SIAM J. Matrix Analysis Applications , vol.31 , Issue.3 , pp. 1235-1256
    • Liu, Z.1    Vandenberghe, L.2
  • 19
    • 84878567534 scopus 로고    scopus 로고
    • Nuclear norm system identification with missing inputs and outputs
    • Z. Liu, A. Hansson, and L. Vandenberghe. Nuclear norm system identification with missing inputs and outputs. Systems & Control Letters, 62(8): 605-612, 2013.
    • (2013) Systems & Control Letters , vol.62 , Issue.8 , pp. 605-612
    • Liu, Z.1    Hansson, A.2    Vandenberghe, L.3
  • 21
    • 41049114357 scopus 로고    scopus 로고
    • Structured low-rank approximation and its applications
    • I. Markovsky. Structured low-rank approximation and its applications. Automatica, 44(4): 891-909, 2008.
    • (2008) Automatica , vol.44 , Issue.4 , pp. 891-909
    • Markovsky, I.1
  • 22
    • 78549288866 scopus 로고    scopus 로고
    • Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization
    • B. Recht, M. Fazel, and P. A. Parrilo. Guaranteed minimum-rank solutions of linear matrix equations via nuclear norm minimization. SIAM Review, 52(3): 471-501, 2010.
    • (2010) SIAM Review , vol.52 , Issue.3 , pp. 471-501
    • Recht, B.1    Fazel, M.2    Parrilo, P.A.3
  • 23
    • 31844451557 scopus 로고    scopus 로고
    • Fast maximum margin matrix factorization for collaborative prediction
    • J. D. M. Rennie and N. Srebro. Fast maximum margin matrix factorization for collaborative prediction. In ICML, pages 713-719, 2005.
    • (2005) ICML , pp. 713-719
    • Rennie, J.D.M.1    Srebro, N.2
  • 25
    • 84941057895 scopus 로고    scopus 로고
    • An SVD-free approach to a class of structured low rank matrix optimization problems with application to system identification
    • ESTA-SISTA
    • M. Signoretto, V. Cevher, and J. A. Suykens. An SVD-free approach to a class of structured low rank matrix optimization problems with application to system identification. Technical report, K.U. Leuven, 2013. 13-44, ESTA-SISTA.
    • (2013) Technical Report, K.U. Leuven , pp. 13-44
    • Signoretto, M.1    Cevher, V.2    Suykens, J.A.3
  • 27
    • 84877780790 scopus 로고    scopus 로고
    • Accelerated training for matrix-norm regularization: A boosting approach
    • X. Zhang, Y. Yu, and D. Schuurmans. Accelerated training for matrix-norm regularization: A boosting approach. In NIPS, pages 2915-2923, 2012.
    • (2012) NIPS , pp. 2915-2923
    • Zhang, X.1    Yu, Y.2    Schuurmans, D.3
  • 28
    • 84937891000 scopus 로고    scopus 로고
    • Multi-task learning: Theory, algorithms, and applications
    • J. Zhou, J. Chen, and J. Ye. Multi-task learning: theory, algorithms, and applications. SIAM Data Mining Tutorial, 2012.
    • (2012) SIAM Data Mining Tutorial
    • Zhou, J.1    Chen, J.2    Ye, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.