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    ICIP
    2007
    IEEE
    192views Image Processing» more  ICIP 2007»
    Image Denoising with Nonparametric Hidden Markov Trees
    14 years 6 months ago
    Image Denoising with Nonparametric Hidden Markov Trees
    Download  www.cs.berkeley.edu
    We develop a hierarchical, nonparametric statistical model for wavelet representations of natural images. Extending previous work on Gaussian scale mixtures, wavelet coefficients ...
    Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jord...
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    NIPS
    2007
    150views Information Technology» more  NIPS 2007»
    Collective Inference on Markov Models for Modeling Bird Migration
    13 years 6 months ago
    Collective Inference on Markov Models for Modeling Bird Migration
    Download  web.engr.oregonstate.edu
    We investigate a family of inference problems on Markov models, where many sample paths are drawn from a Markov chain and partial information is revealed to an observer who attemp...
    Daniel Sheldon, M. A. Saleh Elmohamed, Dexter Koze...
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    BMCBI
    2007
    94views more  BMCBI 2007»
    A Hidden Markov Model to estimate population mixture and allelic copy-numbers in cancers using Affymetrix SNP arrays
    13 years 5 months ago
    A Hidden Markov Model to estimate population mixture and allelic copy-numbers in cancers using Affymetrix SNP arrays
    Download  www.biomedcentral.com
    Background: Affymetrix SNP arrays can interrogate thousands of SNPs at the same time. This allows us to look at the genomic content of cancer cells and to investigate the underlyi...
    Philippe Lamy, Claus L. Andersen, Lars Dyrskjot, N...
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    CSDA
    2007
    116views more  CSDA 2007»
    Exploring the state sequence space for hidden Markov and semi-Markov chains
    13 years 5 months ago
    Exploring the state sequence space for hidden Markov and semi-Markov chains
    Download  www-sop.inria.fr
    The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categ...
    Yann Guédon
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    ICML
    1999
    IEEE
    163views Machine Learning» more  ICML 1999»
    Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
    14 years 6 months ago
    Monte Carlo Hidden Markov Models: Learning Non-Parametric Models of Partially Observable Stochastic Processes
    Download  www.ri.cmu.edu
    We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
    Sebastian Thrun, John Langford, Dieter Fox
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