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    PAMI
    2000
    86views more  PAMI 2000»
    Training Hidden Markov Models with Multiple Observations-A Combinatorial Method
    13 years 4 months ago
    Training Hidden Markov Models with Multiple Observations-A Combinatorial Method
    Download  vision.gel.ulaval.ca
    Xiaolin Li, Marc Parizeau, Réjean Plamondon
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    BMCBI
    2007
    130views more  BMCBI 2007»
    HMM-ModE - Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying e
    13 years 5 months ago
    HMM-ModE - Improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying e
    Download  www.biomedcentral.com
    Background: Profile Hidden Markov Models (HMM) are statistical representations of protein families derived from patterns of sequence conservation in multiple alignments and have b...
    Prashant K. Srivastava, Dhwani K. Desai, Soumyadee...
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    ISMB
    1993
    113views Computational Biology» more  ISMB 1993»
    Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families
    13 years 6 months ago
    Using Dirichlet Mixture Priors to Derive Hidden Markov Models for Protein Families
    Download  reference.kfupm.edu.sa
    A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein familyor the columns of a multiple alignment of that famil...
    Michael Brown, Richard Hughey, Anders Krogh, I. Sa...
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    PRL
    2007
    131views more  PRL 2007»
    A new look at discriminative training for hidden Markov models
    13 years 4 months ago
    A new look at discriminative training for hidden Markov models
    Download  research.microsoft.com
    ct 7 Discriminative training for hidden Markov models (HMMs) has been a central theme in speech recognition research for many years. 8 One most popular technique is minimum classiï...
    Xiaodong He, Li Deng
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    NIPS
    2008
    142views Information Technology» more  NIPS 2008»
    Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
    13 years 6 months ago
    Extracting State Transition Dynamics from Multiple Spike Trains with Correlated Poisson HMM
    Download  books.nips.cc
    Neural activity is non-stationary and varies across time. Hidden Markov Models (HMMs) have been used to track the state transition among quasi-stationary discrete neural states. W...
    Kentaro Katahira, Jun Nishikawa, Kazuo Okanoya, Ma...
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