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Volumn 23, Issue , 2012, Pages

A method of moments for mixture models and hidden markov models

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; HIDDEN MARKOV MODELS; METHOD OF MOMENTS;

EID: 84893458195     PISSN: 15324435     EISSN: 15337928     Source Type: Journal    
DOI: None     Document Type: Conference Paper
Times cited : (79)

References (40)
  • 1
    • 33748603939 scopus 로고    scopus 로고
    • On spectral learning of mixtures of distributions
    • D. Achlioptas and F. McSherry. On spectral learning of mixtures of distributions. In COLT, 2005.
    • (2005) COLT
    • Achlioptas, D.1    Mcsherry, F.2
  • 2
    • 0036495139 scopus 로고    scopus 로고
    • Strong converse for identification via quantum channels
    • R. Ahlswede and A. Winter. Strong converse for identification via quantum channels. IEEE Transactions on Information Theory, 48(3):569-579, 2002.
    • (2002) IEEE Transactions on Information Theory , vol.48 , Issue.3 , pp. 569-579
    • Ahlswede, R.1    Winter, A.2
  • 3
    • 0034830274 scopus 로고    scopus 로고
    • Learning mixtures of arbitrary gaussians
    • S. Arora and R. Kannan. Learning mixtures of arbitrary Gaussians. In STOC, 2001.
    • (2001) STOC
    • Arora, S.1    Kannan, R.2
  • 4
    • 78751519918 scopus 로고    scopus 로고
    • Polynomial learning of distribution families
    • M. Belkin and K. Sinha. Polynomial learning of distribution families. In FOCS, 2010.
    • (2010) FOCS
    • Belkin, M.1    Sinha, K.2
  • 5
    • 51949086515 scopus 로고    scopus 로고
    • Correlational spectral clustering
    • M. B. Blaschko and C. H. Lampert. Correlational spectral clustering. In CVPR, 2008.
    • (2008) CVPR
    • Blaschko, M.B.1    Lampert, C.H.2
  • 7
    • 57949105623 scopus 로고    scopus 로고
    • Isotropic PCA and affine-invariant clustering
    • S. C. Brubaker and S. Vempala. Isotropic PCA and affine-invariant clustering. In FOCS, 2008.
    • (2008) FOCS
    • Brubaker, S.C.1    Vempala, S.2
  • 8
    • 0030588055 scopus 로고    scopus 로고
    • Full reconstruction of markov models on evolutionary trees: Identifiability and consistency
    • J. T. Chang. Full reconstruction of Markov models on evolutionary trees: Identifiability and consistency. Mathematical Biosciences, 137:51-73, 1996.
    • (1996) Mathematical Biosciences , vol.137 , pp. 51-73
    • Chang, J.T.1
  • 9
    • 84898062517 scopus 로고    scopus 로고
    • Learning mixtures of product distributions using correlations and independence
    • K. Chaudhuri and S. Rao. Learning mixtures of product distributions using correlations and independence. In COLT, 2008.
    • (2008) COLT
    • Chaudhuri, K.1    Rao, S.2
  • 11
    • 84863403791 scopus 로고    scopus 로고
    • Learning mixutres of gaussians
    • S. Dasgupta. Learning mixutres of Gaussians. In FOCS, 1999.
    • (1999) FOCS
    • Dasgupta, S.1
  • 12
    • 0037236821 scopus 로고    scopus 로고
    • An elementary proof of a theorem of johnson and lindenstrauss
    • S. Dasgupta and A. Gupta. An elementary proof of a theorem of Johnson and Lindenstrauss. Random Structures and Algorithms, 22(1):60-65, 2003.
    • (2003) Random Structures and Algorithms , vol.22 , Issue.1 , pp. 60-65
    • Dasgupta, S.1    Gupta, A.2
  • 13
    • 33847128516 scopus 로고    scopus 로고
    • A probabilistic analysis of EM for mixtures of separated, spherical gaussians
    • Feb
    • S. Dasgupta and L. Schulman. A probabilistic analysis of EM for mixtures of separated, spherical Gaussians. Journal of Machine Learning Research, 8(Feb):203-226, 2007.
    • (2007) Journal of Machine Learning Research , vol.8 , pp. 203-226
    • Dasgupta, S.1    Schulman, L.2
  • 14
    • 33746050575 scopus 로고    scopus 로고
    • Learning mixtures of product distributions over discrete domains
    • J. Feldman, R. O'Donnell, and R. Servedio. Learning mixtures of product distributions over discrete domains. In FOCS, 2005.
    • (2005) FOCS
    • Feldman, J.1    O'Donnell, R.2    Servedio, R.3
  • 15
    • 55249083012 scopus 로고    scopus 로고
    • PAC learning mixtures of axis-aligned gaussians with no separation assumption
    • J. Feldman, R. O'Donnell, and R. Servedio. PAC learning mixtures of axis-aligned Gaussians with no separation assumption. In COLT, 2006.
    • (2006) COLT
    • Feldman, J.1    O'Donnell, R.2    Servedio, R.3
  • 20
    • 84898066687 scopus 로고    scopus 로고
    • A spectral algorithm for learning hidden markov models
    • D. Hsu, S. M. Kakade, and T. Zhang. A spectral algorithm for learning hidden Markov models. In COLT, 2009.
    • (2009) COLT
    • Hsu, D.1    Kakade, S.M.2    Zhang, T.3
  • 22
    • 0042826822 scopus 로고    scopus 로고
    • Independent component analysis: Algorithms and applications
    • A. Hyv̈arinen and E. Oja. Independent component analysis: Algorithms and applications. Neural Networks, 13(4-5):411-430, 2000.
    • (2000) Neural Networks , vol.13 , Issue.4-5 , pp. 411-430
    • Hyv̈arinen, A.1    Oja, E.2
  • 23
    • 0034198996 scopus 로고    scopus 로고
    • Observable operator models for discrete stochastic time series
    • H. Jaeger. Observable operator models for discrete stochastic time series. Neural Computation, 12 (6), 2000.
    • (2000) Neural Computation , vol.12 , Issue.6
    • Jaeger, H.1
  • 24
    • 77954731171 scopus 로고    scopus 로고
    • Efficiently learning mixtures of two gaussians
    • A. T. Kalai, A. Moitra, and G. Valiant. Efficiently learning mixtures of two Gaussians. In STOC, 2010.
    • (2010) STOC
    • Kalai, A.T.1    Moitra, A.2    Valiant, G.3
  • 25
    • 33746066585 scopus 로고    scopus 로고
    • The spectral method for general mixture models
    • R. Kannan, H. Salmasian, and S. Vempala. The spectral method for general mixture models. In COLT, 2005.
    • (2005) COLT
    • Kannan, R.1    Salmasian, H.2    Vempala, S.3
  • 26
    • 0001402114 scopus 로고
    • Moment matrices: Applications in mixtures
    • B. G. Lindsay. Moment matrices: Applications in mixtures. Annals of Statistics, 17(2):722-740, 1989.
    • (1989) Annals of Statistics , vol.17 , Issue.2 , pp. 722-740
    • Lindsay, B.G.1
  • 29
    • 0035186726 scopus 로고    scopus 로고
    • Spectral partitioning of random graphs
    • F. McSherry. Spectral partitioning of random graphs. In FOCS, 2001.
    • (2001) FOCS
    • Mcsherry, F.1
  • 30
    • 78751527010 scopus 로고    scopus 로고
    • Settling the polynomial learnability of mixtures of gaussians
    • A. Moitra and G. Valiant. Settling the polynomial learnability of mixtures of Gaussians. In FOCS, 2010.
    • (2010) FOCS
    • Moitra, A.1    Valiant, G.2
  • 31
    • 33746918412 scopus 로고    scopus 로고
    • Learning nonsingular phylogenies and hidden markov models
    • E. Mossel and S. Roch. Learning nonsingular phylogenies and hidden Markov models. Annals of Applied Probability, 16(2):583-614, 2006.
    • (2006) Annals of Applied Probability , vol.16 , Issue.2 , pp. 583-614
    • Mossel, E.1    Roch, S.2
  • 32
    • 64249149689 scopus 로고    scopus 로고
    • Learning a parallelepiped: Cryptanalysis of GGH and NTRU signatures
    • P. Q. Nguyen and O. Regev. Learning a parallelepiped: Cryptanalysis of GGH and NTRU signatures. Journal of Cryptology, 22(2):139-160, 2009.
    • (2009) Journal of Cryptology , vol.22 , Issue.2 , pp. 139-160
    • Nguyen, P.Q.1    Regev, O.2
  • 35
    • 0021404166 scopus 로고
    • Mixture densities, maximum likelihood and the EM algorithm
    • R. A. Redner and H. F. Walker. Mixture densities, maximum likelihood and the EM algorithm. SIAM Review, 26(2):195-239, 1984.
    • (1984) SIAM Review , vol.26 , Issue.2 , pp. 195-239
    • Redner, R.A.1    Walker, H.F.2
  • 36
    • 50549180615 scopus 로고
    • On the definition of a family of automata
    • M. P. Scḧutzenberger. On the definition of a family of automata. Information and Control, 4: 245-270, 1961.
    • (1961) Information and Control , vol.4 , pp. 245-270
    • Scḧutzenberger, M.P.1
  • 39
    • 0036957867 scopus 로고    scopus 로고
    • A spectral algorithm for learning mixtures of distributions
    • S. Vempala and G. Wang. A spectral algorithm for learning mixtures of distributions. In FOCS, 2002.
    • (2002) FOCS
    • Vempala, S.1    Wang, G.2
  • 40
    • 84938533326 scopus 로고    scopus 로고
    • Introduction to the non-asymptotic analysis of random matrices
    • Y. Eldar and G. Kutyniok, editors, chapter 5, Cambridge University Press
    • R. Vershynin. Introduction to the non-asymptotic analysis of random matrices. In Y. Eldar and G. Kutyniok, editors, Compressed Sensing, Theory and Applications, chapter 5, pages 210-268. Cambridge University Press, 2012.
    • (2012) Compressed Sensing, Theory and Applications , pp. 210-268
    • Vershynin, R.1


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