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    AAAI
    1997
    124views Intelligent Agents» more  AAAI 1997»
    Effective Bayesian Inference for Stochastic Programs
    13 years 8 months ago
    Effective Bayesian Inference for Stochastic Programs
    Download  ai.stanford.edu
    In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
    Daphne Koller, David A. McAllester, Avi Pfeffer
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    ATAL
    2006
    Springer
    161views Intelligent Agents» more  ATAL 2006»
    On the complexity of practical ATL model checking
    13 years 11 months ago
    On the complexity of practical ATL model checking
    Download  www.csc.liv.ac.uk
    We investigate the computational complexity of reasoning about multi-agent systems using the cooperation logic ATL of Alur, Henzinger, and Kupferman. It is known that satisfiabili...
    Wiebe van der Hoek, Alessio Lomuscio, Michael Wool...
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    FLOPS
    2006
    Springer
    205views Automated Reasoning» more  FLOPS 2006»
    Contracts as Pairs of Projections
    13 years 11 months ago
    Contracts as Pairs of Projections
    Download  www.eecs.northwestern.edu
    Abstract. Assertion-based contracts provide a powerful mechanism for stating invariants at module boundaries and for enforcing them uniformly. In 2002, Findler and Felleisen showed...
    Robert Bruce Findler, Matthias Blume
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    ENTCS
    2008
    146views more  ENTCS 2008»
    Probabilistic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions
    13 years 7 months ago
    Probabilistic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions
    Download  lanther.co.uk
    istic Abstract Interpretation of Imperative Programs using Truncated Normal Distributions Michael J. A. Smith1 ,2 Laboratory for Foundations of Computer Science University of Edinb...
    Michael J. A. Smith
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    JMLR
    2012
    255views Programming Languages» more  JMLR 2012»
    Learning Low-order Models for Enforcing High-order Statistics
    11 years 10 months ago
    Learning Low-order Models for Enforcing High-order Statistics
    Download  jmlr.csail.mit.edu
    Models such as pairwise conditional random fields (CRFs) are extremely popular in computer vision and various other machine learning disciplines. However, they have limited expre...
    Patrick Pletscher, Pushmeet Kohli
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