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    AAAI
    2006
    111views Intelligent Agents» more  AAAI 2006»
    Memory Intensive Branch-and-Bound Search for Graphical Models
    15 years 2 months ago
    Memory Intensive Branch-and-Bound Search for Graphical Models
    Download  www.ics.uci.edu
    AND/OR search spaces have recently been introduced as a unifying paradigm for advanced algorithmic schemes for graphical models. The main virtue of this representation is its sens...
    Radu Marinescu 0002, Rina Dechter
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    106
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    AIPS
    2006
    171views Artificial Intelligence» more  AIPS 2006»
    Goal Achievement in Partially Known, Partially Observable Domains
    15 years 2 months ago
    Goal Achievement in Partially Known, Partially Observable Domains
    Download  www.aaai.org
    We present a decision making algorithm for agents that act in partially observable domains which they do not know fully. Making intelligent choices in such domains is very difficu...
    Allen Chang, Eyal Amir
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    FLAIRS
    2004
    119views Artificial Intelligence» more  FLAIRS 2004»
    Hidden Layer Training via Hessian Matrix Information
    15 years 2 months ago
    Hidden Layer Training via Hessian Matrix Information
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    The output weight optimization-hidden weight optimization (OWO-HWO) algorithm for training the multilayer perceptron alternately updates the output weights and the hidden weights....
    Changhua Yu, Michael T. Manry, Jiang Li
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    114
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    GEOINFO
    2004
    131views Information Technology» more  GEOINFO 2004»
    Non-Uniform Mesh Simplification Using Adaptative Merge Procedures
    15 years 2 months ago
    Non-Uniform Mesh Simplification Using Adaptative Merge Procedures
    Download  www.geoinfo.info
    : The performance of a walkthrough over terrain models is deeply influenced by the real scenario high level of details. To guarantee natural and smooth changes in a sequence of sce...
    Flávio Mello, Edilberto Strauss, Antonio A....
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    EMNLP
    2006
    190views Natural Language Processing» more  EMNLP 2006»
    Competitive generative models with structure learning for NLP classification tasks
    15 years 2 months ago
    Competitive generative models with structure learning for NLP classification tasks
    Download  nlp.stanford.edu
    In this paper we show that generative models are competitive with and sometimes superior to discriminative models, when both kinds of models are allowed to learn structures that a...
    Kristina Toutanova
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