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    PR
    2010
    129views more  PR 2010»
    Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
    13 years 5 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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    ICML
    2007
    IEEE
    188views Machine Learning» more  ICML 2007»
    Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
    14 years 8 months ago
    Multi-task learning for sequential data via iHMMs and the nested Dirichlet process
    Download  www.machinelearning.org
    A new hierarchical nonparametric Bayesian model is proposed for the problem of multitask learning (MTL) with sequential data. Sequential data are typically modeled with a hidden M...
    Kai Ni, Lawrence Carin, David B. Dunson
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    ICPR
    2008
    IEEE
    146views Computer Vision» more  ICPR 2008»
    Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach
    14 years 1 months ago
    Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach
    Download  figment.cse.usf.edu
    This paper 1 proposes a technique for simplifying a given Gaussian mixture model, i.e. reformulating the density in a more parcimonious manner, if possible (less Gaussian componen...
    Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
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    EOR
    2007
    165views more  EOR 2007»
    Adaptive credit scoring with kernel learning methods
    13 years 7 months ago
    Adaptive credit scoring with kernel learning methods
    Download  www.crc.man.ed.ac.uk
    Credit scoring is a method of modelling potential risk of credit applications. Traditionally, logistic regression, linear regression and discriminant analysis are the most popular...
    Yingxu Yang
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    KDD
    2004
    ACM
    237views Data Mining» more  KDD 2004»
    Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
    14 years 7 months ago
    Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
    Download  www.eh3.uc.edu
    Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
    Mario Medvedovic, Junhai Guo
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