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    BMCBI
    2006
    103views more  BMCBI 2006»
    Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
    13 years 7 months ago
    Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression
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    Background: The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level ...
    Sébastien Lemieux
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    ICML
    1995
    IEEE
    130views Machine Learning» more  ICML 1995»
    TD Models: Modeling the World at a Mixture of Time Scales
    14 years 7 months ago
    TD Models: Modeling the World at a Mixture of Time Scales
    Download  people.hnl.bcm.tmc.edu
    Richard S. Sutton
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    NIPS
    2004
    170views Information Technology» more  NIPS 2004»
    A Harmonic Excitation State-Space Approach to Blind Separation of Speech
    13 years 8 months ago
    A Harmonic Excitation State-Space Approach to Blind Separation of Speech
    Download  books.nips.cc
    We discuss an identification framework for noisy speech mixtures. A block-based generative model is formulated that explicitly incorporates the time-varying harmonic plus noise (H...
    Rasmus Kongsgaard Olsson, Lars Kai Hansen
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    CIKM
    2004
    Springer
    112views Information Technology» more  CIKM 2004»
    Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model
    14 years 13 days ago
    Unified filtering by combining collaborative filtering and content-based filtering via mixture model and exponential model
    Download  www.cs.cmu.edu
    Collaborative filtering and content-based filtering are two types of information filtering techniques. Combining these two techniques can improve the recommendation effectiveness....
    Luo Si, Rong Jin
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    EMNLP
    2007
    120views Natural Language Processing» more  EMNLP 2007»
    Bayesian Document Generative Model with Explicit Multiple Topics
    13 years 8 months ago
    Bayesian Document Generative Model with Explicit Multiple Topics
    Download  www.r.dl.itc.u-tokyo.ac.jp
    In this paper, we proposed a novel probabilistic generative model to deal with explicit multiple-topic documents: Parametric Dirichlet Mixture Model(PDMM). PDMM is an expansion of...
    Issei Sato, Hiroshi Nakagawa
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