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Volumn 7, Issue SUPPL4, 2013, Pages

Sparse representation approaches for the classification of high-dimensional biological data

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; BIOLOGY; METHODOLOGY;

EID: 84880712800     PISSN: None     EISSN: 17520509     Source Type: Journal    
DOI: 10.1186/1752-0509-7-S4-S6     Document Type: Article
Times cited : (42)

References (28)
  • 1
    • 0033636139 scopus 로고    scopus 로고
    • Support vector machine classification and validation of cancer tissue samples using microarray expression data
    • 10.1093/bioinformatics/16.10.906, 11120680
    • Furey T, Cristianini N, Duffy N, Bednarski D, Schummer M, Haussler D. Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics 2000, 16(10):906-914. 10.1093/bioinformatics/16.10.906, 11120680.
    • (2000) Bioinformatics , vol.16 , Issue.10 , pp. 906-914
    • Furey, T.1    Cristianini, N.2    Duffy, N.3    Bednarski, D.4    Schummer, M.5    Haussler, D.6
  • 2
    • 84886468094 scopus 로고    scopus 로고
    • The regularized linear models and kernels toolbox in MATLAB
    • University of Windsor, Windsor, Ontario
    • Li Y, Ngom A. The regularized linear models and kernels toolbox in MATLAB. Tech. rep., School of Computer Science 2013, University of Windsor, Windsor, Ontario., https://sites.google.com/site/rlmktool
    • (2013) Tech. rep., School of Computer Science
    • Li, Y.1    Ngom, A.2
  • 3
    • 2542430932 scopus 로고    scopus 로고
    • Singular value decomposition and principal component analysis
    • Kluwer, Berrar D, Dubitzky W, Granzow M, Norwell, MA
    • Wall M, Rechtsteiner A, Rocha L. Singular value decomposition and principal component analysis. A Practical Approach to Microarray Data Analysis 2003, 91-109. Kluwer, Berrar D, Dubitzky W, Granzow M, Norwell, MA.
    • (2003) A Practical Approach to Microarray Data Analysis , pp. 91-109
    • Wall, M.1    Rechtsteiner, A.2    Rocha, L.3
  • 4
    • 62549125109 scopus 로고    scopus 로고
    • High-dimensional sparse factor modeling: applications in gene expression genomics
    • 10.1198/016214508000000869, 3017385, 21218139
    • Carvalho C, Chang J, Lucas J, Nevins J, Wang Q, West M. High-dimensional sparse factor modeling: applications in gene expression genomics. Journal of the American Statistical Association 2008, 103(484):1438-1456. 10.1198/016214508000000869, 3017385, 21218139.
    • (2008) Journal of the American Statistical Association , vol.103 , Issue.484 , pp. 1438-1456
    • Carvalho, C.1    Chang, J.2    Lucas, J.3    Nevins, J.4    Wang, Q.5    West, M.6
  • 6
    • 84881233012 scopus 로고    scopus 로고
    • Representation learning: a review and new perspectives
    • 1206.5538v2
    • Bengio Y, Courville A, Vincent P. Representation learning: a review and new perspectives. Arxiv 2012, 1206.5538v2.
    • (2012) Arxiv
    • Bengio, Y.1    Courville, A.2    Vincent, P.3
  • 7
    • 33845584374 scopus 로고    scopus 로고
    • Image denoising via learned dictionaries and sparse representation
    • Washington DC: IEEE
    • Elad M, Aharon M. Image denoising via learned dictionaries and sparse representation. CVPR, IEEE Computer Society 2006, 895-900. Washington DC: IEEE.
    • (2006) CVPR, IEEE Computer Society , pp. 895-900
    • Elad, M.1    Aharon, M.2
  • 8
    • 84876097941 scopus 로고    scopus 로고
    • The non-negative matrix factorization toolbox for biological data mining
    • 10.1186/1751-0473-8-10, 3736608, 23591137
    • Li Y, Ngom A. The non-negative matrix factorization toolbox for biological data mining. BMC Source Code for Biology and Medicine 2013, 8:10. 10.1186/1751-0473-8-10, 3736608, 23591137.
    • (2013) BMC Source Code for Biology and Medicine , vol.8 , pp. 10
    • Li, Y.1    Ngom, A.2
  • 9
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • 10.1038/44565, 10548103
    • Lee DD, Seung S. Learning the parts of objects by non-negative matrix factorization. Nature 1999, 401:788-791. 10.1038/44565, 10548103.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, S.2
  • 11
    • 65349171459 scopus 로고    scopus 로고
    • Sparse representation for classification of tumors using gene expression data
    • 2655631, 19300522
    • Hang X, Wu FX. Sparse representation for classification of tumors using gene expression data. J. Biomedicine and Biotechnology 2009, 2009:ID 403689. 2655631, 19300522.
    • (2009) J. Biomedicine and Biotechnology , vol.2009
    • Hang, X.1    Wu, F.X.2
  • 13
    • 0242295767 scopus 로고    scopus 로고
    • Bayesian factor regression models in the "large p, small n" paradigm
    • West M. Bayesian factor regression models in the "large p, small n" paradigm. Bayesian Statistics 2003, 7:723-732.
    • (2003) Bayesian Statistics , vol.7 , pp. 723-732
    • West, M.1
  • 14
    • 59749104367 scopus 로고    scopus 로고
    • From sparse solutions of systems of equations to sparse modeling of signals and images
    • Bruckstein AM, Donoho DL, Elad M. From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Review 2009, 51:34-81.
    • (2009) SIAM Review , vol.51 , pp. 34-81
    • Bruckstein, A.M.1    Donoho, D.L.2    Elad, M.3
  • 16
    • 80955131778 scopus 로고    scopus 로고
    • Kernel sparse representation based classification
    • Yin J, Liu X, Jin Z, Yang W. Kernel sparse representation based classification. Neurocomputing 2012, 77:120-128.
    • (2012) Neurocomputing , vol.77 , pp. 120-128
    • Yin, J.1    Liu, X.2    Jin, Z.3    Yang, W.4
  • 17
    • 78149343905 scopus 로고    scopus 로고
    • Kernel sparse representation for image classification and face recognition
    • Springer
    • Gao S, Tsang IWH, Chia LT. Kernel sparse representation for image classification and face recognition. ECCV 2010, 1-14. Springer.
    • (2010) ECCV , pp. 1-14
    • Gao, S.1    Tsang, I.W.H.2    Chia, L.T.3
  • 18
    • 0030779611 scopus 로고    scopus 로고
    • Sparse coding with an overcomplete basis set: a strategy employed by V1?
    • 10.1016/S0042-6989(97)00169-7, 9425546
    • Olshausen B, Field D. Sparse coding with an overcomplete basis set: a strategy employed by V1?. Vision Research 1997, 37(23):3311-3325. 10.1016/S0042-6989(97)00169-7, 9425546.
    • (1997) Vision Research , vol.37 , Issue.23 , pp. 3311-3325
    • Olshausen, B.1    Field, D.2
  • 19
    • 61549128441 scopus 로고    scopus 로고
    • Robust face recognition via sparse representation
    • Wright J, Yang A, Ganesh A, Sastry SS, Ma Y. Robust face recognition via sparse representation. TPAMI 2009, 31(2):210-227.
    • (2009) TPAMI , vol.31 , Issue.2 , pp. 210-227
    • Wright, J.1    Yang, A.2    Ganesh, A.3    Sastry, S.S.4    Ma, Y.5
  • 23
    • 80052234083 scopus 로고    scopus 로고
    • Proximal methods for hierarchical sparse coding
    • Jenatton R, Mairal J, Obozinski G, Bach F. Proximal methods for hierarchical sparse coding. JMLR 2011, 12(2011):2297-2334.
    • (2011) JMLR , vol.12 , Issue.2011 , pp. 2297-2334
    • Jenatton, R.1    Mairal, J.2    Obozinski, G.3    Bach, F.4
  • 24
    • 33646874546 scopus 로고    scopus 로고
    • The molecular portraits of breast tumors are conserved across microarray platforms
    • 10.1186/1471-2164-7-96, 1468408, 16643655
    • Hu Z, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics 2006, 7:96. 10.1186/1471-2164-7-96, 1468408, 16643655.
    • (2006) BMC Genomics , vol.7 , pp. 96
    • Hu, Z.1
  • 25
    • 0037120949 scopus 로고    scopus 로고
    • Serum proteomic patterns for detection of prostate cancer
    • 10.1093/jnci/94.20.1576, 12381711
    • Petricoin EI, et al. Serum proteomic patterns for detection of prostate cancer. J. National Cancer Institute 2002, 94(20):1576-1578. 10.1093/jnci/94.20.1576, 12381711.
    • (2002) J. National Cancer Institute , vol.94 , Issue.20 , pp. 1576-1578
    • Petricoin, E.I.1
  • 26
    • 84871617105 scopus 로고    scopus 로고
    • Convex and semi-nonnegative matrix factorizations
    • Ding C, Li T, Jordan MI. Convex and semi-nonnegative matrix factorizations. TPAMI 2010, 32:45-55.
    • (2010) TPAMI , vol.32 , pp. 45-55
    • Ding, C.1    Li, T.2    Jordan, M.I.3
  • 27
    • 84884470016 scopus 로고    scopus 로고
    • The sparse representation toolbox in MATLAB
    • The sparse representation toolbox in MATLAB., https://sites.google.com/site/sparsereptool


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.