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    » Gaussian Processes for Machine Learning
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    ICONIP
    2009
    153views Information Technology» more  ICONIP 2009»
    Learning Gaussian Process Models from Uncertain Data
    15 years 10 days ago
    Learning Gaussian Process Models from Uncertain Data
    Download  damas.ift.ulaval.ca
    It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
    Patrick Dallaire, Camille Besse, Brahim Chaib-draa
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    ML
    2002
    ACM
    220views Machine Learning» more  ML 2002»
    Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
    15 years 2 months ago
    Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
    Download  www.mth.kcl.ac.uk
    I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
    Peter Sollich
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    ICML
    1998
    IEEE
    133views Machine Learning» more  ICML 1998»
    Using Learning for Approximation in Stochastic Processes
    16 years 3 months ago
    Using Learning for Approximation in Stochastic Processes
    Download  robotics.stanford.edu
    Daphne Koller, Raya Fratkina
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    ICALT
    2010
    IEEE
    129views Machine Learning» more  ICALT 2010»
    Learning Technology Standards Adoption Process Improvement and Output Legitimacy
    15 years 3 months ago
    Learning Technology Standards Adoption Process Improvement and Output Legitimacy
    Download  hoel.nu
    Paul A. Hollins, Tore Hoel
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    107
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    ICML
    2002
    IEEE
    218views Machine Learning» more  ICML 2002»
    An epsilon-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes
    16 years 3 months ago
    An epsilon-Optimal Grid-Based Algorithm for Partially Observable Markov Decision Processes
    Download  www.cs.ucf.edu
    Blai Bonet
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