메뉴 건너뛰기




Volumn 3971 LNCS, Issue , 2006, Pages 1214-1221

A comparative study on selection of cluster number and local subspace dimension in the mixture PCA models

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; MATHEMATICAL MODELS; PARAMETER ESTIMATION; PROBABILITY; PROBLEM SOLVING; STATISTICAL METHODS;

EID: 33745905639     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11759966_180     Document Type: Conference Paper
Times cited : (1)

References (16)
  • 1
    • 0345109524 scopus 로고
    • Beyond PCA learning: From linear to nonlinear and from global representation to local representation
    • Seoul, Korea
    • Xu, L.: Beyond PCA Learning: From Linear to Nonlinear and From Global Representation to Local Representation. In: Proc. Intl. Conf. on Neural Information Processing (ICONIP94). Volume 2., Seoul, Korea (1994) 943-949
    • (1994) Proc. Intl. Conf. on Neural Information Processing (ICONIP94) , vol.2 , pp. 943-949
    • Xu, L.1
  • 2
    • 0028752267 scopus 로고
    • Theories for unsupervised learning: PCA and its nonlinear extensions
    • Orlando, Florida
    • Xu, L.: Theories for Unsupervised Learning: PCA and Its Nonlinear Extensions. In: Proc. of IEEE ICNN94. Volume II., Orlando, Florida (1994) 1252-1257
    • (1994) Proc. of IEEE ICNN94 , vol.2 , pp. 1252-1257
    • Xu, L.1
  • 3
    • 0005906827 scopus 로고
    • Bayesian-Kullback coupled Ying-Yang machines: Unified leanings and new results on vector quantization
    • Beijing, China
    • Xu, L.: Bayesian-Kullback Coupled Ying-Yang Machines: Unified Leanings and New Results on Vector Quantization. In: Proc. Intl. Conf. on Neural Information Processing (ICONIP95), Beijing, China (1995) 977-988
    • (1995) Proc. Intl. Conf. on Neural Information Processing (ICONIP95) , pp. 977-988
    • Xu, L.1
  • 4
    • 0033556788 scopus 로고    scopus 로고
    • Mixtures of probabilistic principal component analysers
    • Tipping, M.E., Bishop, C.M.: Mixtures of Probabilistic Principal Component Analysers, Neural Computation 11 (1999) 443-482
    • (1999) Neural Computation , vol.11 , pp. 443-482
    • Tipping, M.E.1    Bishop, C.M.2
  • 5
    • 3843095548 scopus 로고    scopus 로고
    • Independent component analysis and extensions with noise and time: A Bayesian Ying-Yang learning perspective
    • Xu, L.: Independent Component Analysis and Extensions with Noise and Time: A Bayesian Ying-Yang Learning Perspective. Neural Information Processing Letters and Reviews 1 (2003) 1-52
    • (2003) Neural Information Processing Letters and Reviews , vol.1 , pp. 1-52
    • Xu, L.1
  • 6
    • 0016355478 scopus 로고
    • A new look at statistical model identification
    • Akaike, H.: A New Look at Statistical Model Identification. IEEE Transactions on Automatic Control 19 (1974) 716-723
    • (1974) IEEE Transactions on Automatic Control , vol.19 , pp. 716-723
    • Akaike, H.1
  • 7
    • 34250108028 scopus 로고
    • Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
    • Bozdogan, H.: Model Selection and Akaike's Information Criterion (AIC): The General Theory and Its Analytical Extensions. Psychometrika 52 (1987) 345-370
    • (1987) Psychometrika , vol.52 , pp. 345-370
    • Bozdogan, H.1
  • 8
    • 0018015137 scopus 로고
    • Modeling by shortest data description
    • Rissanen, J.: Modeling by Shortest Data Description. Automatica 14 (1978) 465-471
    • (1978) Automatica , vol.14 , pp. 465-471
    • Rissanen, J.1
  • 9
    • 0032183995 scopus 로고    scopus 로고
    • The minimum description length principle in coding and modeling
    • Barron, A., Rissanen, J.: The Minimum Description Length Principle in Coding and Modeling. IEEE Trans. Information Theory 44 (1998) 2743-2760
    • (1998) IEEE Trans. Information Theory , vol.44 , pp. 2743-2760
    • Barron, A.1    Rissanen, J.2
  • 10
    • 3843136240 scopus 로고    scopus 로고
    • Advances on BYY harmony learning: Information theoretic perspective, generalized projection geometry, and independent factor auto-determination
    • Xu, L.: Advances on BYY Harmony Learning: Information Theoretic Perspective, Generalized Projection Geometry, and Independent Factor Auto-determination. IEEE Trans on Neural Networks 15 (2004) 885-902
    • (2004) IEEE Trans on Neural Networks , vol.15 , pp. 885-902
    • Xu, L.1
  • 11
    • 3843056324 scopus 로고    scopus 로고
    • Bayesian Ying Yang learning (I): A unified perspective for statistical modeling
    • Zhong, N., Liu, J., eds.: Springer
    • Xu, L.: Bayesian Ying Yang Learning (I): A Unified Perspective for Statistical Modeling. In Zhong, N., Liu, J., eds.: Intelligent Technologies for Information Analysis, Springer (2004) 615-659
    • (2004) Intelligent Technologies for Information Analysis , pp. 615-659
    • Xu, L.1
  • 12
    • 24344441147 scopus 로고    scopus 로고
    • Bayesian Ying Yang learning (II): A new mechanism for model selection and regularization
    • Zhong, N., Liu, J., eds.: Springer
    • Xu, L.: Bayesian Ying Yang Learning (II): A New Mechanism for Model Selection and Regularization. In Zhong, N., Liu, J., eds.: Intelligent Technologies for Information Analysis, Springer (2004) 661-706
    • (2004) Intelligent Technologies for Information Analysis , pp. 661-706
    • Xu, L.1
  • 13
    • 84898929664 scopus 로고    scopus 로고
    • EM algorithms for PCA and SPCA
    • Jordan, M.I., Kearns, M.J., Solla, S.A., eds.: The MIT Press
    • Roweis, S.: EM Algorithms for PCA and SPCA. In Jordan, M.I., Kearns, M.J., Solla, S.A., eds.: Advances in Neural Information Processing Systems. Volume 10., The MIT Press (1998) 626-632
    • (1998) Advances in Neural Information Processing Systems , vol.10 , pp. 626-632
    • Roweis, S.1
  • 15
    • 33845722419 scopus 로고
    • Factor analysis and AIC
    • Akaike, H.: Factor Analysis and AIC. Psychometrika 52 (1987) 317-332
    • (1987) Psychometrika , vol.52 , pp. 317-332
    • Akaike, H.1
  • 16
    • 0036790879 scopus 로고    scopus 로고
    • BYY harmony learning, structural RPCL, and topological self-organizing on mixture models
    • Xu, L.: BYY Harmony Learning, Structural RPCL, and Topological Self-Organizing on Mixture Models. Neural Networks 15 (2002) 1125-1151
    • (2002) Neural Networks , vol.15 , pp. 1125-1151
    • Xu, L.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.