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    NIPS
    1992
    153views Information Technology» more  NIPS 1992»
    Hidden Markov Model} Induction by Bayesian Model Merging
    14 years 11 months ago
    Hidden Markov Model} Induction by Bayesian Model Merging
    Download  www.ark.cs.cmu.edu
    This paper describes a technique for learning both the number of states and the topologyof Hidden Markov Models from examples. The inductionprocess starts with the most specific m...
    Andreas Stolcke, Stephen M. Omohundro
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    SAC
    2011
    ACM
    244views Applied Computing» more  SAC 2011»
    A quasi-Newton acceleration for high-dimensional optimization algorithms
    14 years 4 months ago
    A quasi-Newton acceleration for high-dimensional optimization algorithms
    Download  dalexander.bol.ucla.edu
    Abstract In many statistical problems, maximum likelihood estimation by an EM or MM algorithm suffers from excruciatingly slow convergence. This tendency limits the application of ...
    Hua Zhou, David Alexander, Kenneth Lange
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    ICDM
    2006
    IEEE
    145views Data Mining» more  ICDM 2006»
    Stability Region Based Expectation Maximization for Model-based Clustering
    15 years 3 months ago
    Stability Region Based Expectation Maximization for Model-based Clustering
    Download  www.cs.wayne.edu
    In spite of the initialization problem, the ExpectationMaximization (EM) algorithm is widely used for estimating the parameters in several data mining related tasks. Most popular ...
    Chandan K. Reddy, Hsiao-Dong Chiang, Bala Rajaratn...
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    AAAI
    2006
    165views Intelligent Agents» more  AAAI 2006»
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    14 years 11 months ago
    Mixtures of Predictive Linear Gaussian Models for Nonlinear, Stochastic Dynamical Systems
    Download  www.aaai.org
    The Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent parame...
    David Wingate, Satinder P. Singh
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    BMCBI
    2005
    98views more  BMCBI 2005»
    Iterative approach to model identification of biological networks
    14 years 9 months ago
    Iterative approach to model identification of biological networks
    Download  www.biomedcentral.com
    Background: Recent advances in molecular biology techniques provide an opportunity for developing detailed mathematical models of biological processes. An iterative scheme is intr...
    Kapil G. Gadkar, Rudiyanto Gunawan, Francis J. Doy...
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