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    PAMI
    2008
    179views more  PAMI 2008»
    Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
    13 years 9 months ago
    Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
    Download  www.svcl.ucsd.edu
    A dynamic texture is a spatio-temporal generative model for video, which represents video sequences as observations from a linear dynamical system. This work introduces the mixtur...
    Antoni B. Chan, Nuno Vasconcelos
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    PR
    2010
    129views more  PR 2010»
    Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
    13 years 8 months ago
    Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
    Download  hal.archives-ouvertes.fr
    Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
    Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
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    KDD
    2010
    ACM
    326views Data Mining» more  KDD 2010»
    Document clustering via dirichlet process mixture model with feature selection
    13 years 7 months ago
    Document clustering via dirichlet process mixture model with feature selection
    Download  math.nankai.edu.cn
    One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
    Guan Yu, Ruizhang Huang, Zhaojun Wang
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    EMMCVPR
    1999
    Springer
    124views Computer Vision» more  EMMCVPR 1999»
    On Fitting Mixture Models
    14 years 2 months ago
    On Fitting Mixture Models
    Download  www.lx.it.pt
    Consider the problem of tting a nite Gaussian mixture, with an unknown number of components, to observed data. This paper proposes a new minimum description length (MDL) type crite...
    Mário A. T. Figueiredo, José M. N. L...
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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 11 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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