메뉴 건너뛰기




Volumn 4029 LNAI, Issue , 2006, Pages 548-562

Extended SMART algorithms for non-negative matrix factorization invited paper

Author keywords

[No Author keywords available]

Indexed keywords

ALGEBRA; COMPUTATIONAL GEOMETRY; CONVERGENCE OF NUMERICAL METHODS; DIGITAL ARITHMETIC; FUNCTIONS; MATRIX ALGEBRA; OPTIMIZATION;

EID: 33746239350     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11785231_58     Document Type: Conference Paper
Times cited : (85)

References (30)
  • 1
    • 0033592606 scopus 로고    scopus 로고
    • Learning of the parts of objects by non-negative matrix factorization
    • Lee, D.D., Seung, H.S.: Learning of the parts of objects by non-negative matrix factorization. Nature 401 (1999) 788-791.
    • (1999) Nature , vol.401 , pp. 788-791
    • Lee, D.D.1    Seung, H.S.2
  • 2
    • 18444370569 scopus 로고    scopus 로고
    • Nonnegative features of spectro-temporal sounds for classification
    • Cho, Y.C., Choi, S.: Nonnegative features of spectro-temporal sounds for classification. Pattern Recognition Letters 26 (2005) 1327-1336.
    • (2005) Pattern Recognition Letters , vol.26 , pp. 1327-1336
    • Cho, Y.C.1    Choi, S.2
  • 3
    • 1242263422 scopus 로고    scopus 로고
    • Recovery of constituent spectra using non-negative matrix factorization
    • Wavelets: Applications in Signal and Image Processing
    • Sajda, P., Du, S., Parra, L.: Recovery of constituent spectra using non-negative matrix factorization. In: Proceedings of SPIE - Volume 5207, Wavelets: Applications in Signal and Image Processing (2003) 321-331.
    • (2003) Proceedings of SPIE , vol.5207 , pp. 321-331
    • Sajda, P.1    Du, S.2    Parra, L.3
  • 4
    • 0041339710 scopus 로고    scopus 로고
    • Introducing a weighted nonnegative matrix factorization for image classification
    • Guillamet, D., Vitri'a, J., Schiele, B.: Introducing a weighted nonnegative matrix factorization for image classification. Pattern Recognition Letters 24 (2004) 2447 -2454
    • (2004) Pattern Recognition Letters , vol.24 , pp. 2447-2454
    • Guillamet, D.1    Vitri'a, J.2    Schiele, B.3
  • 5
    • 33746217035 scopus 로고    scopus 로고
    • Non-negative matrix factorization with orthogonality constraints for chemical agent detection in Raman spectra
    • Mystic USA
    • Li, H., Adali, T., W. Wang, D.E.: Non-negative matrix factorization with orthogonality constraints for chemical agent detection in Raman spectra. In: IEEE Workshop on Machine Learning for Signal Processing), Mystic USA (2005)
    • (2005) IEEE Workshop on Machine Learning for Signal Processing
    • Li, H.1    Adali, T.W.2    Wang, D.E.3
  • 6
    • 33745683306 scopus 로고    scopus 로고
    • Csiszar's divergences for non-negative matrix factorization: Family of new algorithms
    • Cichocki, A., Zdunek, R., Amari, S.: Csiszar's divergences for non-negative matrix factorization: Family of new algorithms. Springer LNCS 3889 (2006) 32-39
    • (2006) Springer LNCS , vol.3889 , pp. 32-39
    • Cichocki, A.1    Zdunek, R.2    Amari, S.3
  • 7
    • 0028561099 scopus 로고
    • Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values
    • Paatero, P., Tapper, U.: Positive matrix factorization: A nonnegative factor model with optimal utilization of error estimates of data values. Environmetrics 5 (1994) 111-126
    • (1994) Environmetrics , vol.5 , pp. 111-126
    • Paatero, P.1    Tapper, U.2
  • 9
    • 84900510076 scopus 로고    scopus 로고
    • Non-negative matrix factorization with sparseness constraints
    • Hoyer, P.: Non-negative matrix factorization with sparseness constraints. Journal of Machine Learning Research 5 (2004) 1457-1469.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 1457-1469
    • Hoyer, P.1
  • 10
    • 33745701339 scopus 로고    scopus 로고
    • A generalized divergence measure for nonnegative matrix factorization
    • Torun, Poland
    • Kompass, R.: A generalized divergence measure for nonnegative matrix factorization, Neuroinfomatics Workshop, Torun, Poland (2005)
    • (2005) Neuroinfomatics Workshop
    • Kompass, R.1
  • 11
    • 84864031935 scopus 로고    scopus 로고
    • Generalized nonnegative matrix approximations with Bregman divergences
    • Vancouver Canada
    • Dhillon, I., Sra, S.: Generalized nonnegative matrix approximations with Bregman divergences. In: NIPS -Neural Information Proc. Systems, Vancouver Canada. (2005)
    • (2005) NIPS -Neural Information Proc. Systems
    • Dhillon, I.1    Sra, S.2
  • 14
    • 0034854666 scopus 로고    scopus 로고
    • Use of nonnegative matrix factorization for language model adaptation in a lecture transcription task
    • Salt Lake City, UT
    • Novak, M., Mammone, R.: Use of nonnegative matrix factorization for language model adaptation in a lecture transcription task. In: Proceedings of the 2001 IEEE Conference on Acoustics, Speech and Signal Processing. Volume 1., Salt Lake City, UT (2001) 541-544
    • (2001) Proceedings of the 2001 IEEE Conference on Acoustics, Speech and Signal Processing , vol.1 , pp. 541-544
    • Novak, M.1    Mammone, R.2
  • 19
    • 33746265328 scopus 로고    scopus 로고
    • An interior-point gradient method for large-scale totally nonnegative least squares problems
    • Department of Computational and Applied Mathematics, Rice University, Houston, Texas, USA
    • Merritt, M., Zhang, Y.: An interior-point gradient method for large-scale totally nonnegative least squares problems. Technical report, Department of Computational and Applied Mathematics, Rice University, Houston, Texas, USA (2004)
    • (2004) Technical Report
    • Merritt, M.1    Zhang, Y.2
  • 20
    • 0040673441 scopus 로고    scopus 로고
    • Robust blind source separation by beta-divergence
    • Minami, M., Eguchi, S.: Robust blind source separation by beta-divergence. Neural Computation 14 (2002) 1859-1886
    • (2002) Neural Computation , vol.14 , pp. 1859-1886
    • Minami, M.1    Eguchi, S.2
  • 22
    • 0141642753 scopus 로고
    • Information measures: A critical survey
    • Academia Prague
    • Csiszár, I.: Information measures: A critical survey. In: Prague Conference on Information Theory, Academia Prague. Volume A. (1974) 73-86.
    • (1974) Prague Conference on Information Theory , vol.A , pp. 73-86
    • Csiszár, I.1
  • 24
    • 85041123735 scopus 로고    scopus 로고
    • Divergence function, duality and convex analysis
    • Zhang, J.: Divergence function, duality and convex analysis. Neural Computation 16 (2004) 159-195.
    • (2004) Neural Computation , vol.16 , pp. 159-195
    • Zhang, J.1
  • 25
    • 14844349201 scopus 로고    scopus 로고
    • Gradient-based manipulation of non-parametric entropy estimates
    • Schraudolf, N.: Gradient-based manipulation of non-parametric entropy estimates. IEEE Trans, on Neural Networks 16 (2004) 159-195.
    • (2004) IEEE Trans, on Neural Networks , vol.16 , pp. 159-195
    • Schraudolf, N.1
  • 26
    • 0031675604 scopus 로고    scopus 로고
    • Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative (RBI) methods
    • Byrne, C.: Accelerating the EMML algorithm and related iterative algorithms by rescaled block-iterative (RBI) methods. IEEE Transactions on Image Processing 7 (1998) 100-109.
    • (1998) IEEE Transactions on Image Processing , vol.7 , pp. 100-109
    • Byrne, C.1
  • 27
    • 14844366632 scopus 로고    scopus 로고
    • Choosing parameters in block-iterative or ordered subset reconstruction algorithms
    • Byrne, C.: Choosing parameters in block-iterative or ordered subset reconstruction algorithms. IEEE Transactions on Image Progressing 14 (2005) 321-327
    • (2005) IEEE Transactions on Image Progressing , vol.14 , pp. 321-327
    • Byrne, C.1
  • 29
    • 0029587111 scopus 로고
    • Information geometry of the em and em algorithms for neural networks
    • Amari, S.: Information geometry of the EM and em algorithms for neural networks. Neural Networks 8 (1995) 1379-1408.
    • (1995) Neural Networks , vol.8 , pp. 1379-1408
    • Amari, S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.