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    CSDA
    2008
    71views more  CSDA 2008»
    On the estimation of a large sparse Bayesian system: The Snaer program
    13 years 5 months ago
    On the estimation of a large sparse Bayesian system: The Snaer program
    Download  www.e.u-tokyo.ac.jp
    Dmitry Danilov, Jan R. Magnus
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    IJCAI
    2007
    201views Artificial Intelligence» more  IJCAI 2007»
    Using Linear Programming for Bayesian Exploration in Markov Decision Processes
    13 years 6 months ago
    Using Linear Programming for Bayesian Exploration in Markov Decision Processes
    Download  www.cs.mcgill.ca
    A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
    Pablo Samuel Castro, Doina Precup
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    TSP
    2010
    175views Artificial Intelligence» more  TSP 2010»
    Variance-component based sparse signal reconstruction and model selection
    12 years 11 months ago
    Variance-component based sparse signal reconstruction and model selection
    Download  home.eng.iastate.edu
    We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
    Kun Qiu, Aleksandar Dogandzic
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    CVPR
    2004
    IEEE
    212views Computer Vision» more  CVPR 2004»
    Learning a Restricted Bayesian Network for Object Detection
    14 years 7 months ago
    Learning a Restricted Bayesian Network for Object Detection
    Download  www.ri.cmu.edu
    Many classes of images have the characteristics of sparse structuring of statistical dependency and the presence of conditional independencies among various groups of variables. S...
    Henry Schneiderman
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    NIPS
    2007
    202views Information Technology» more  NIPS 2007»
    A New View of Automatic Relevance Determination
    13 years 6 months ago
    A New View of Automatic Relevance Determination
    Download  books.nips.cc
    Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
    David P. Wipf, Srikantan S. Nagarajan
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