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    NIPS
    2000
    110views Information Technology» more  NIPS 2000»
    Sparse Representation for Gaussian Process Models
    15 years 8 months ago
    Sparse Representation for Gaussian Process Models
    Download  reference.kfupm.edu.sa
    We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...
    Lehel Csató, Manfred Opper
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    ANOR
    2002
    57views more  ANOR 2002»
    Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing
    15 years 6 months ago
    Redefining Event Variables for Efficient Modeling of Continuous-Time Batch Processing
    Download  opim.wharton.upenn.edu
    Abstract: We define events so as to reduce the number of events and decision variables needed for modeling batchscheduling problems such as described in [Westenberger and Kallrath ...
    Siqun Wang, Monique Guignard
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    ICASSP
    2008
    IEEE
    234views Signal Processing» more  ICASSP 2008»
    A hierarchical point process model for speech recognition
    16 years 1 months ago
    A hierarchical point process model for speech recognition
    Download  people.cs.uchicago.edu
    Aren Jansen, Partha Niyogi
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    ICASSP
    2010
    IEEE
    172views Signal Processing» more  ICASSP 2010»
    Detection-based speech recognition with sparse point process models
    15 years 7 months ago
    Detection-based speech recognition with sparse point process models
    Download  www.clsp.jhu.edu
    Aren Jansen, Partha Niyogi
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    EMNLP
    2011
    156views Natural Language Processing» more  EMNLP 2011»
    Discovering Morphological Paradigms from Plain Text Using a Dirichlet Process Mixture Model
    14 years 6 months ago
    Discovering Morphological Paradigms from Plain Text Using a Dirichlet Process Mixture Model
    Download  www.cs.jhu.edu
    Markus Dreyer, Jason Eisner
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