메뉴 건너뛰기




Volumn 37, Issue 2, 2015, Pages 383-393

Fast nonparametric clustering of structured time-series

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS; INFERENCE ENGINES;

EID: 84920982448     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2014.2318711     Document Type: Article
Times cited : (46)

References (30)
  • 1
    • 0000396062 scopus 로고    scopus 로고
    • Natural gradient works efficiently in learning
    • S. Amari, "Natural gradient works efficiently in learning," Neural Comput., vol. 10, no. 2, pp. 251-276, 1998.
    • (1998) Neural Comput. , vol.10 , Issue.2 , pp. 251-276
    • Amari, S.1
  • 2
    • 21644455755 scopus 로고    scopus 로고
    • Hierarchical models for assessing variability among functions
    • S. Behseta, R. E. Kass, and G. L. Wallstrom, "Hierarchical models for assessing variability among functions," Biometrika, vol. 92, no. 2, pp. 419-434, 2005.
    • (2005) Biometrika , vol.92 , Issue.2 , pp. 419-434
    • Behseta, S.1    Kass, R.E.2    Wallstrom, G.L.3
  • 3
    • 84867186048 scopus 로고    scopus 로고
    • Variational inference for Dirichlet process mixtures
    • D. M. Blei and M. I. Jordan, "Variational inference for Dirichlet process mixtures," Bayesian Anal., vol. 1, no. 1, pp. 121-144, 2006.
    • (2006) Bayesian Anal. , vol.1 , Issue.1 , pp. 121-144
    • Blei, D.M.1    Jordan, M.I.2
  • 4
    • 80053928843 scopus 로고    scopus 로고
    • Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements
    • E. Cooke, R. Savage, P. Kirk, R. Darkins, and D. Wild, "Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements," BMC Bioinformat., vol. 12, no. 1, p. 399, http://www.biomedcentral.com/1471-2105/12/399, 2011.
    • (2011) BMC Bioinformat. , vol.12 , Issue.1 , pp. 399
    • Cooke, E.1    Savage, R.2    Kirk, P.3    Darkins, R.4    Wild, D.5
  • 5
    • 70350094855 scopus 로고    scopus 로고
    • Nonparametric Bayes applications to biostatistics
    • L. Hjort, C. Holmes, P. Muller, and S. Walker, Eds. Cambridge, U.K.: Cambridge Univ Press
    • D. Dunson, "Nonparametric Bayes applications to biostatistics," in Bayesian Nonparametrics, L. Hjort, C. Holmes, P. Muller, and S. Walker, Eds. Cambridge, U.K.: Cambridge Univ Press, 2010.
    • (2010) Bayesian Nonparametrics
    • Dunson, D.1
  • 8
    • 84920987579 scopus 로고    scopus 로고
    • Hierarchial Bayesian modelling of gene expression time series
    • Submitted to
    • J. Hensman, N. Lawrence, and M. Rattray, "Hierarchial Bayesian modelling of gene expression time series," Submitted to BMC Bioinformat., 2012.
    • (2012) BMC Bioinformat.
    • Hensman, J.1    Lawrence, N.2    Rattray, M.3
  • 12
    • 79551487646 scopus 로고    scopus 로고
    • Approximate Riemannian conjugate gradient learning for fixedform variational Bayes
    • A. Honkela, T. Raiko, M. Kuusela, M. Tornio, and J. Karhunen, "Approximate Riemannian conjugate gradient learning for fixedform variational Bayes," J. Mach. Learn. Res., vol. 9999, pp. 3235- 3268, 2010.
    • (2010) J. Mach. Learn. Res. , vol.9999 , pp. 3235-3268
    • Honkela, A.1    Raiko, T.2    Kuusela, M.3    Tornio, M.4    Karhunen, J.5
  • 13
    • 1842486852 scopus 로고    scopus 로고
    • A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model
    • S. Jain and R. Neal, "A split-merge Markov chain Monte Carlo procedure for the Dirichlet process mixture model," J. Comput. Graph. Statist., vol. 13, no. 1, pp. 158-182, 2004.
    • (2004) J. Comput. Graph. Statist. , vol.13 , Issue.1 , pp. 158-182
    • Jain, S.1    Neal, R.2
  • 14
    • 79956211692 scopus 로고    scopus 로고
    • A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression
    • A. Kalaitzis and N. Lawrence, "A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression," BMC Bioinformat., vol. 12, no. 1, p. 180, 2011.
    • (2011) BMC Bioinformat. , vol.12 , Issue.1 , pp. 180
    • Kalaitzis, A.1    Lawrence, N.2
  • 16
    • 33750291245 scopus 로고    scopus 로고
    • Fast variational inference for Gaussian process models through KL-correction
    • N. King and N. D. Lawrence, "Fast variational inference for Gaussian process models through KL-correction," in Proc. 17th Eur. Conf. Mach. Learn., 2006, pp. 270-281.
    • (2006) Proc. 17th Eur. Conf. Mach. Learn. , pp. 270-281
    • King, N.1    Lawrence, N.D.2
  • 18
    • 70449373407 scopus 로고    scopus 로고
    • A gradientbased algorithm competitive with variational Bayesian em for mixture of Gaussians
    • M. Kuusela, T. Raiko, A. Honkela, and J. Karhunen, "A gradientbased algorithm competitive with variational Bayesian EM for mixture of Gaussians," in Proc. Int. Joint Conf. Neural Netw., 2009, pp. 1688-1695.
    • (2009) Proc. Int. Joint Conf. Neural Netw. , pp. 1688-1695
    • Kuusela, M.1    Raiko, T.2    Honkela, A.3    Karhunen, J.4
  • 20
    • 83655184780 scopus 로고    scopus 로고
    • Overlapping mixtures of Gaussian processes for the data association problem
    • M. L-azaro-Gredilla, S. Van Vaerenbergh, and N. Lawrence, "Overlapping mixtures of Gaussian processes for the data association problem," Pattern Recognit., vol. 45, pp. 1386-1395, 2011.
    • (2011) Pattern Recognit. , vol.45 , pp. 1386-1395
    • L-Azaro-Gredilla, M.1    Van Vaerenbergh, S.2    Lawrence, N.3
  • 21
    • 3042686005 scopus 로고    scopus 로고
    • Bayesian mixture model based clustering of replicated microarray data
    • M. Medvedovic, K. Yeung, and R. Bumgarner, "Bayesian mixture model based clustering of replicated microarray data," Bioinformat., vol. 20, no. 8, pp. 1222-1232, 2004.
    • (2004) Bioinformat. , vol.20 , Issue.8 , pp. 1222-1232
    • Medvedovic, M.1    Yeung, K.2    Bumgarner, R.3
  • 22
    • 84876833306 scopus 로고    scopus 로고
    • Hierarchical Gaussian process regression
    • S. Park and S. Choi, "Hierarchical Gaussian process regression," in Proc. 2nd Asian Conf. Mach. Learn., 2010, vol. 13, pp. 95-110.
    • (2010) Proc. 2nd Asian Conf. Mach. Learn. , vol.13 , pp. 95-110
    • Park, S.1    Choi, S.2
  • 26
    • 0000147488 scopus 로고    scopus 로고
    • Online model selection based on the variational Bayes
    • M. A. Sato, "Online model selection based on the variational Bayes," Neural Comput., vol. 13, no. 7, pp. 1649-1681, 2001.
    • (2001) Neural Comput. , vol.13 , Issue.7 , pp. 1649-1681
    • Sato, M.A.1
  • 27
    • 77950803115 scopus 로고    scopus 로고
    • A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series
    • O. Stegle, K. Denby, E. Cooke, D. Wild, Z. Ghahramani, and K. Borgwardt, "A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series," J. Comput. Biol., vol. 17, no. 3, pp. 355-367, 2010.
    • (2010) J. Comput. Biol. , vol.17 , Issue.3 , pp. 355-367
    • Stegle, O.1    Denby, K.2    Cooke, E.3    Wild, D.4    Ghahramani, Z.5    Borgwardt, K.6
  • 29
    • 84864061876 scopus 로고    scopus 로고
    • A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation
    • Y. W. Teh, D. Newman, and M. Welling, "A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation," in Proc. Adv. Neural Inf. Process. Syst., 2007, vol. 19, p. 1353.
    • (2007) Proc. Adv. Neural Inf. Process. Syst. , vol.19 , pp. 1353
    • Teh, Y.W.1    Newman, D.2    Welling, M.3
  • 30
    • 0034244838 scopus 로고    scopus 로고
    • Split and merge em algorithm for improving Gaussian mixture density estimates
    • N. Ueda, R. Nakano, Z. Ghahramani, and G. Hinton, "Split and merge EM algorithm for improving Gaussian mixture density estimates," J. VLSI Signal Process., vol. 26, no. 1, pp. 133-140, 2000.
    • (2000) J. VLSI Signal Process. , vol.26 , Issue.1 , pp. 133-140
    • Ueda, N.1    Nakano, R.2    Ghahramani, Z.3    Hinton, G.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.