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Volumn 5212 LNAI, Issue PART 2, 2008, Pages 266-281

Large-scale clustering through functional embedding

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTERING ALGORITHMS; DATABASE SYSTEMS; DIFFRACTIVE OPTICAL ELEMENTS; FLOW OF SOLIDS; OPTIMIZATION; ROBOT LEARNING;

EID: 56049108171     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-87481-2_18     Document Type: Conference Paper
Times cited : (7)

References (31)
  • 2
    • 33749035690 scopus 로고    scopus 로고
    • Scalable clustering algorithms with balancing constraints
    • Banerjee, A., Gosh, J.: Scalable clustering algorithms with balancing constraints. Data Mining and Knowledge Discovery 13(3), 365-395 (2006)
    • (2006) Data Mining and Knowledge Discovery , vol.13 , Issue.3 , pp. 365-395
    • Banerjee, A.1    Gosh, J.2
  • 3
    • 0042378381 scopus 로고    scopus 로고
    • Laplacian eigenmaps for dimensionality reduction and data representation
    • Belkin, M., Niyogi, P.: Laplacian eigenmaps for dimensionality reduction and data representation. Neural Computation 15(6), 1373-1396 (2003)
    • (2003) Neural Computation , vol.15 , Issue.6 , pp. 1373-1396
    • Belkin, M.1    Niyogi, P.2
  • 4
    • 33750729556 scopus 로고    scopus 로고
    • Manifold regularization: A geometric framework for learning from Labeled and Unlabeled Examples
    • Belkin, M., Niyogi, P., Sindhwani, V.: Manifold regularization: a geometric framework for learning from Labeled and Unlabeled Examples. Journal of Machine Learning Research 7, 2399-2434 (2006)
    • (2006) Journal of Machine Learning Research , vol.7 , pp. 2399-2434
    • Belkin, M.1    Niyogi, P.2    Sindhwani, V.3
  • 8
    • 33947180792 scopus 로고    scopus 로고
    • Stochastic learning
    • Bousquet, O, von Luxburg, U, Rätsch, G, eds, Machine Learning 2003, Springer. Heidelberg
    • Bottou, L.: Stochastic learning. In: Bousquet, O., von Luxburg, U., Rätsch, G. (eds.) Machine Learning 2003. LNCS (LNAI). vol. 3176, pp. 146-168. Springer. Heidelberg (2004)
    • (2004) LNCS (LNAI , vol.3176 , pp. 146-168
    • Bottou, L.1
  • 10
    • 51949086172 scopus 로고    scopus 로고
    • Chapelle, O., Zien, A.: Semi-supervised classification by low density separation. In: AISTATS. pp. 57-64 (January 2005)
    • Chapelle, O., Zien, A.: Semi-supervised classification by low density separation. In: AISTATS. pp. 57-64 (January 2005)
  • 13
    • 84898035178 scopus 로고    scopus 로고
    • Neural network modeling of spectral embedding
    • Gong, H.F., Pan, C., Yang, Q., Lu, H.Q., Ma, S.: Neural network modeling of spectral embedding. In: BMVC 2006, p. 1-227 (2006)
    • (2006) BMVC 2006 , pp. 1-227
    • Gong, H.F.1    Pan, C.2    Yang, Q.3    Lu, H.Q.4    Ma, S.5
  • 15
    • 0026925324 scopus 로고
    • New spectral methods for ratio cut partitioning and clustering
    • Hagen, L., Kahng, A.: New spectral methods for ratio cut partitioning and clustering. IEEE Trans. on Computer Aided-Design 11(9), 1074-1085 (1992)
    • (1992) IEEE Trans. on Computer Aided-Design , vol.11 , Issue.9 , pp. 1074-1085
    • Hagen, L.1    Kahng, A.2
  • 20
    • 56049112139 scopus 로고    scopus 로고
    • Ng, A.Y., Jordan, M., Weiss, Y.: On spectral clustering: analysis and an algorithm. In: Advances in Neural Information Processing Systems (NIPS 13) (2001)
    • Ng, A.Y., Jordan, M., Weiss, Y.: On spectral clustering: analysis and an algorithm. In: Advances in Neural Information Processing Systems (NIPS 13) (2001)
  • 21
    • 0034704222 scopus 로고    scopus 로고
    • Nonlinear dimensionality reduction by locally linear embedding
    • Roweis, S.T., Saul. L.K.: Nonlinear dimensionality reduction by locally linear embedding. Science 290(5500), 2323-2326 (2000)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2323-2326
    • Roweis, S.T.1    Saul, L.K.2
  • 23
    • 0347243182 scopus 로고    scopus 로고
    • Nonlinear component analysis as a kernel eigenvalue problem
    • Schölkopf, B., Smola, A.J.. Müller, K.R.: Nonlinear component analysis as a kernel eigenvalue problem. Neural Computation 10, 1299-1319 (1998)
    • (1998) Neural Computation , vol.10 , pp. 1299-1319
    • Schölkopf, B.1    Smola, A.J.2    Müller, K.R.3
  • 25
    • 0034704229 scopus 로고    scopus 로고
    • A global geometric framework for nonlinear dimensionality reduction
    • Tenenbaum, J.B., de Silva, V., Langford, J.C.: A global geometric framework for nonlinear dimensionality reduction. Science 290(5500), 2319-2323 (2000)
    • (2000) Science , vol.290 , Issue.5500 , pp. 2319-2323
    • Tenenbaum, J.B.1    de Silva, V.2    Langford, J.C.3
  • 26
    • 79952394649 scopus 로고    scopus 로고
    • The out-of-sample problem for multidimensional scaling
    • Technical Report 06-04, Dept. of Statistics, Indiana University
    • Trosset, M.W., Priebe, C.E.: The out-of-sample problem for multidimensional scaling. Technical Report 06-04, Dept. of Statistics, Indiana University (2006)
    • (2006)
    • Trosset, M.W.1    Priebe, C.E.2
  • 27
    • 56049086888 scopus 로고    scopus 로고
    • Verma, D., Meila, M.: Comparison of spectral clustering methods. In: Advances in Neural Information Processing Systems (NIPS 15) (2003)
    • Verma, D., Meila, M.: Comparison of spectral clustering methods. In: Advances in Neural Information Processing Systems (NIPS 15) (2003)
  • 29
    • 56049122733 scopus 로고    scopus 로고
    • Wu, M., Schölkopf, B.: A local learning approach for clustering. In: Advances in Neural Information Processing Systems (NIPS 19) (2006)
    • Wu, M., Schölkopf, B.: A local learning approach for clustering. In: Advances in Neural Information Processing Systems (NIPS 19) (2006)
  • 30
    • 56049122949 scopus 로고    scopus 로고
    • Xu, L., Neufeld, J., Larson, B., Schuurmans, D.: Maximum margin clustering. In: Advances in Neural Information Processing Systems (NIPS 16) (2004)
    • Xu, L., Neufeld, J., Larson, B., Schuurmans, D.: Maximum margin clustering. In: Advances in Neural Information Processing Systems (NIPS 16) (2004)


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