메뉴 건너뛰기




Volumn , Issue PART 1, 2013, Pages 231-239

Fast conical hull algorithms for near-separable non-negative matrix factorization

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; LEARNING SYSTEMS;

EID: 84894650699     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (133)

References (27)
  • 1
    • 84862609231 scopus 로고    scopus 로고
    • Computing a nonnegative matrix factorization - Provably
    • Arora, Sanjeev, Ge, Rong, Kannan, Ravi, and Moitra, Ankur. Computing a nonnegative matrix factorization - provably. In STOC, 2012a.
    • (2012) STOC
    • Arora, S.1    Ge, R.2    Kannan, R.3    Moitra, A.4
  • 2
    • 84871960604 scopus 로고    scopus 로고
    • Learning topic models - Going beyond svd
    • Arora, Sanjeev, Ge, Rong, and Moitra, Ankur. Learning topic models - going beyond svd. In FOCS, 2012b.
    • (2012) FOCS
    • Arora, S.1    Ge, R.2    Moitra, A.3
  • 3
    • 85162015690 scopus 로고    scopus 로고
    • CUR from a sparse optimization viewpoint
    • Bien, J., Xu, Y., and Mahoney, M. CUR from a sparse optimization viewpoint. In NIPS, 2010.
    • (2010) NIPS
    • Bien, J.1    Xu, Y.2    Mahoney, M.3
  • 4
    • 84877774066 scopus 로고    scopus 로고
    • Factoring nonnegative matrices with linear programs
    • Bittorf, Victor, Recht, Benjamin, Re, Christopher, and Tropp, Joel A. Factoring nonnegative matrices with linear programs. In NIPS, 2012.
    • (2012) NIPS
    • Bittorf, V.1    Recht, B.2    Re, C.3    Tropp, J.A.4
  • 7
    • 33747462885 scopus 로고
    • More output-sensitive geometric algorithms
    • Clarkson, K. More output-sensitive geometric algorithms. In FOCS, 1994.
    • (1994) FOCS
    • Clarkson, K.1
  • 8
    • 23744456750 scopus 로고    scopus 로고
    • When does non-negative matrix factorization give a correct decomposition into parts?
    • Donoho, D. and Stodden, V. When does non-negative matrix factorization give a correct decomposition into parts? In NIPS, 2003.
    • (2003) NIPS
    • Donoho, D.1    Stodden, V.2
  • 9
    • 0043111773 scopus 로고    scopus 로고
    • An algorithm for identifying the frame of a pointed finite conical hull
    • Dula, J. H., Hegalson, R. V., and Venugopal, N. An algorithm for identifying the frame of a pointed finite conical hull. INFORMS Jour. on Comp., 10(3):323-330, 1998. (Pubitemid 128669137)
    • (1998) INFORMS Journal on Computing , vol.10 , Issue.3 , pp. 323-330
    • Dula, J.H.1    Helgasom, R.V.2    Venugopal, N.3
  • 10
    • 84866685721 scopus 로고    scopus 로고
    • See all by looking at a few: Sparse modeling for finding representative objects
    • Elhamifar, Ehsan, Sapiro, Guillermo, and Vidal, Rene. See all by looking at a few: Sparse modeling for finding representative objects. In CVPR, 2012.
    • (2012) CVPR
    • Elhamifar, E.1    Sapiro, G.2    Vidal, R.3
  • 11
    • 84862519707 scopus 로고    scopus 로고
    • A convex model for non-negative matrix factorization and dimensionality reduction on physical space
    • Esser, Ernie, Mller, Michael, Osher, Stanley, Sapiro, Guillermo, and Xin, Jack. A convex model for non-negative matrix factorization and dimensionality reduction on physical space. IEEE Transactions on Image Processing, 21(10):3239-3252, 2012.
    • (2012) IEEE Transactions on Image Processing , vol.21 , Issue.10 , pp. 3239-3252
    • Esser, E.1    Mller, M.2    Osher, S.3    Sapiro, G.4    Xin, J.5
  • 14
    • 33749254467 scopus 로고    scopus 로고
    • Practical solutions to the problem of diagonal dominance in kernel document clustering
    • Greene, Derek and Cunningham, Padraig. Practical solutions to the problem of diagonal dominance in kernel document clustering. In ICML, 2006.
    • (2006) ICML
    • Greene, D.1    Cunningham, P.2
  • 15
    • 80052651461 scopus 로고    scopus 로고
    • Fast coordinate descent methods with variable selection for non-negative matrix factorization
    • Hsieh, C. J. and Dhillon, I. S. Fast coordinate descent methods with variable selection for non-negative matrix factorization. In KDD, 2011.
    • (2011) KDD
    • Hsieh, C.J.1    Dhillon, I.S.2
  • 18
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D. and Seung, S. Learning the parts of objects by non-negative matrix factorization. Nature, 401 (6755):788-791, 1999.
    • (1999) Nature , vol.401 , Issue.6755 , pp. 788-791
    • Lee, D.1    Seung, S.2
  • 19
    • 84897509098 scopus 로고    scopus 로고
    • Lemur, http://lemurproject.org/clueweb09/.
  • 20
    • 84876811202 scopus 로고    scopus 로고
    • RCV1: A new benchmark collection for text categorization research
    • Lewis, D, Yang, Y, Rose, T, and Li, F. RCV1: A new benchmark collection for text categorization research. Journal Of Machine Learning Research, 5:361-397, 2004.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 361-397
    • Lewis, D.1    Yang, Y.2    Rose, T.3    Li, F.4
  • 21
    • 35548969471 scopus 로고    scopus 로고
    • Projected gradient methods for non-negative matrix factorization
    • Lin, C.-J. Projected gradient methods for non-negative matrix factorization. Neural Computation, 2007.
    • (2007) Neural Computation
    • Lin, C.-J.1
  • 23
    • 84897559999 scopus 로고    scopus 로고
    • archive.ics.uci.edu/ml/datasets/Reuters-21578+Tex
    • Reuters. archive.ics.uci.edu/ml/datasets/Reuters- 21578+Text+Categorization+Collection.
    • Reuters
  • 24
    • 84897473650 scopus 로고    scopus 로고
    • TDT2. http://www.itl.nist.gov/iad/mig/tests/tdt/1998/.
    • TDT2
  • 25
    • 30844461481 scopus 로고    scopus 로고
    • Algorithms for simultaneous sparse approximation. Part II: Convex relaxation
    • DOI 10.1016/j.sigpro.2005.05.031, PII S0165168405002239, Sparse Approximations in Signal and Image Processing
    • Tropp, J. A. Algorithms for simultaneous sparse approximation. part ii: Convex relaxation. Signal Processing, 86:589-602, 2006. (Pubitemid 43106573)
    • (2006) Signal Processing , vol.86 , Issue.3 , pp. 589-602
    • Tropp, J.A.1
  • 26
    • 30844445842 scopus 로고    scopus 로고
    • Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit
    • DOI 10.1016/j.sigpro.2005.05.030, PII S0165168405002227, Sparse Approximations in Signal and Image Processing
    • Tropp, J. A., Gilbert, A. C., and Strauss, M. J. Algorithms for simultaneous sparse approximation. part i: Greedy pursuit. Signal Processing, 86:572-588, 2006. (Pubitemid 43106572)
    • (2006) Signal Processing , vol.86 , Issue.3 , pp. 572-588
    • Tropp, J.A.1    Gilbert, A.C.2    Strauss, M.J.3
  • 27
    • 73249153369 scopus 로고    scopus 로고
    • On the complexity of non-negative matrix factorization
    • Vavasis, S. On the complexity of non-negative matrix factorization. SIAM Journal on Optimization, 20 (3):1364-, 2009.
    • (2009) SIAM Journal on Optimization , vol.20 , Issue.3 , pp. 1364
    • Vavasis, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.