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    ASE
    1998
    81views more  ASE 1998»
    Program Understanding as Constraint Satisfaction: Representation and Reasoning Techniques
    13 years 6 months ago
    Program Understanding as Constraint Satisfaction: Representation and Reasoning Techniques
    Download  www.cse.ust.hk
    The process of understanding a source code in a high-level programming language involves complex computation. Given a piece of legacy code and a library of program plan templates, ...
    Steven G. Woods, Qiang Yang
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    BMCBI
    2010
    116views more  BMCBI 2010»
    A hybrid approach to protein folding problem integrating constraint programming with local search
    13 years 6 months ago
    A hybrid approach to protein folding problem integrating constraint programming with local search
    Download  www.biomedcentral.com
    Background: The protein folding problem remains one of the most challenging open problems in computational biology. Simplified models in terms of lattice structure and energy func...
    Abu Zafer M. Dayem Ullah, Kathleen Steinhöfel
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    ICML
    2009
    IEEE
    163views Machine Learning» more  ICML 2009»
    Structure learning of Bayesian networks using constraints
    14 years 7 months ago
    Structure learning of Bayesian networks using constraints
    Download  www.ecse.rpi.edu
    This paper addresses exact learning of Bayesian network structure from data and expert's knowledge based on score functions that are decomposable. First, it describes useful ...
    Cassio Polpo de Campos, Zhi Zeng, Qiang Ji
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    SPLC
    2008
    115views Software Engineering» more  SPLC 2008»
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    13 years 8 months ago
    Filtered Cartesian Flattening: An Approximation Technique for Optimally Selecting Features while Adhering to Resource Constraint
    Download  www.dre.vanderbilt.edu
    Software Product-lines (SPLs) use modular software components that can be reconfigured into different variants for different requirements sets. Feature modeling is a common method...
    Jules White, B. Doughtery, Douglas C. Schmidt
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    CP
    2006
    Springer
    118views Artificial Intelligence» more  CP 2006»
    : A Bottom-Up Approach for Solving Quantified CSPs
    13 years 10 months ago
    : A Bottom-Up Approach for Solving Quantified CSPs
    Download  www.lirmm.fr
    Abstract. Thanks to its extended expressiveness, the quantified constraint satisfaction problem (QCSP) can be used to model problems that are difficult to express in the standard C...
    Guillaume Verger, Christian Bessière
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