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    ASC
    2006
    103views Artificial Intelligence» more  ASC 2006»
    Simulation-based optimisation using local search and neural network metamodels
    13 years 10 months ago
    Simulation-based optimisation using local search and neural network metamodels
    Download  www.his.se
    This paper presents a new algorithm for enhancing the efficiency of simulation-based optimisation using local search and neural network metamodels. The local search strategy is ba...
    Anna Persson, Henrik Grimm, Amos Ng
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    ML
    2006
    ACM
    142views Machine Learning» more  ML 2006»
    The max-min hill-climbing Bayesian network structure learning algorithm
    13 years 8 months ago
    The max-min hill-climbing Bayesian network structure learning algorithm
    Download  www.dsl-lab.org
    We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
    Ioannis Tsamardinos, Laura E. Brown, Constantin F....
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    BMCBI
    2008
    173views more  BMCBI 2008»
    Improved machine learning method for analysis of gas phase chemistry of peptides
    13 years 8 months ago
    Improved machine learning method for analysis of gas phase chemistry of peptides
    Download  www.biomedcentral.com
    Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
    Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
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    ASPDAC
    2005
    ACM
    99views Hardware» more  ASPDAC 2005»
    A fast counterexample minimization approach with refutation analysis and incremental SAT
    13 years 10 months ago
    A fast counterexample minimization approach with refutation analysis and incremental SAT
    Download  www.ssypub.org
    － It is a hotly research topic to eliminate irrelevant variables from counterexample, to make it easier to be understood. BFL algorithm is the most effective Counterexample minim...
    ShengYu Shen, Ying Qin, Sikun Li
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    CIKM
    2009
    Springer
    170views Information Technology» more  CIKM 2009»
    A general magnitude-preserving boosting algorithm for search ranking
    14 years 3 months ago
    A general magnitude-preserving boosting algorithm for search ranking
    Download  itcs.tsinghua.edu.cn
    Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
    Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
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