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    » On Learning Boolean Functions
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    ICML
    2007
    IEEE
    204views Machine Learning» more  ICML 2007»
    Constructing basis functions from directed graphs for value function approximation
    16 years 21 days ago
    Constructing basis functions from directed graphs for value function approximation
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    Basis functions derived from an undirected graph connecting nearby samples from a Markov decision process (MDP) have proven useful for approximating value functions. The success o...
    Jeffrey Johns, Sridhar Mahadevan
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    AML
    2006
    87views more  AML 2006»
    The modal logic of continuous functions on cantor space
    14 years 12 months ago
    The modal logic of continuous functions on cantor space
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    Abstract Let L be a propositional language with standard Boolean connectives plus two modalities: an S4-ish topological modality and a temporal modality , understood as `next'...
    Philip Kremer
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    DAC
    2005
    ACM
    133views Computer Architecture» more  DAC 2005»
    Efficient SAT solving: beyond supercubes
    16 years 26 days ago
    Efficient SAT solving: beyond supercubes
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    SAT (Boolean satisfiability) has become the primary Boolean reasoning engine for many EDA applications, so the efficiency of SAT solving is of great practical importance. Recently...
    Domagoj Babic, Jesse D. Bingham, Alan J. Hu
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    ICMLA
    2008
    195views Machine Learning» more  ICMLA 2008»
    Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
    15 years 1 months ago
    Basis Function Construction in Reinforcement Learning Using Cascade-Correlation Learning Architecture
    Download  www.grappa.univ-lille3.fr
    In reinforcement learning, it is a common practice to map the state(-action) space to a different one using basis functions. This transformation aims to represent the input data i...
    Sertan Girgin, Philippe Preux
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    ICML
    2009
    IEEE
    120views Machine Learning» more  ICML 2009»
    Fast gradient-descent methods for temporal-difference learning with linear function approximation
    16 years 21 days ago
    Fast gradient-descent methods for temporal-difference learning with linear function approximation
    Download  carbon.videolectures.net
    Csaba Szepesvári, David Silver, Doina Precu...
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