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    » Estimating Likelihoods for Topic Models
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    IPM
    2008
    102views more  IPM 2008»
    Fast exact maximum likelihood estimation for mixture of language model
    13 years 4 months ago
    Fast exact maximum likelihood estimation for mixture of language model
    Download  users.soe.ucsc.edu
    Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...
    Yi Zhang 0001, Wei Xu
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    IEICET
    2008
    110views more  IEICET 2008»
    Language Modeling Using PLSA-Based Topic HMM
    13 years 4 months ago
    Language Modeling Using PLSA-Based Topic HMM
    Download  www.me.cs.scitec.kobe-u.ac.jp
    In this paper, we propose a PLSA-based language model for sports live speech. This model is implemented in unigram rescaling technique that combines a topic model and an n-gram. I...
    Atsushi Sako, Tetsuya Takiguchi, Yasuo Ariki
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    SAC
    2008
    ACM
    126views Applied Computing» more  SAC 2008»
    Particle methods for maximum likelihood estimation in latent variable models
    13 years 4 months ago
    Particle methods for maximum likelihood estimation in latent variable models
    Download  www2.warwick.ac.uk
    Standard methods for maximum likelihood parameter estimation in latent variable models rely on the Expectation-Maximization algorithm and its Monte Carlo variants. Our approach is ...
    Adam M. Johansen, Arnaud Doucet, Manuel Davy
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    CSDA
    2007
    105views more  CSDA 2007»
    GSA-based maximum likelihood estimation for threshold vector error correction model
    13 years 4 months ago
    GSA-based maximum likelihood estimation for threshold vector error correction model
    Download  nlpr-web.ia.ac.cn
    The log-likelihood function of threshold vector error correction models is neither differentiable, nor smooth with respect to some parameters. Therefore, it is very difficult to ...
    Zheng Yang, Zheng Tian, Zixia Yuan
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    CSDA
    2007
    108views more  CSDA 2007»
    Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
    13 years 4 months ago
    Nonlinear random effects mixture models: Maximum likelihood estimation via the EM algorithm
    Download  bmsr.usc.edu
    Nonlinear random effects models with finite mixture structures are used to identify polymorphism in pharmacokinetic/ pharmacodynamic (PK/PD) phenotypes. An EM algorithm for maxim...
    Xiaoning Wang, Alan Schumitzky, David Z. D'Argenio
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