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    DATAMINE
    2007
    110views more  DATAMINE 2007»
    The complexity of non-hierarchical clustering with instance and cluster level constraints
    14 years 9 months ago
    The complexity of non-hierarchical clustering with instance and cluster level constraints
    Download  www.cs.ucdavis.edu
    Recent work has looked at extending clustering algorithms with instance level must-link (ML) and cannot-link (CL) background information. Our work introduces δ and ǫ cluster lev...
    Ian Davidson, S. S. Ravi
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    ENTCS
    2008
    95views more  ENTCS 2008»
    An Experimental Ambiguity Detection Tool
    14 years 9 months ago
    An Experimental Ambiguity Detection Tool
    Download  www.lsv.ens-cachan.fr
    Although programs convey an unambiguous meaning, the grammars used in practice to describe their syntax are often ambiguous, and completed with disambiguation rules. Whether these...
    Sylvain Schmitz
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    VVEIS
    2008
    123views Information Technology» more  VVEIS 2008»
    An Executable Semantics of Object-oriented Models for Simulation and Theorem Proving
    14 years 11 months ago
    An Executable Semantics of Object-oriented Models for Simulation and Theorem Proving
    Download  www.jaist.ac.jp
    This paper presents an executable semantics of OO models. We made it possible to conduct both simulation and theorem proving on the semantics by implementing its underlying heap me...
    Kenro Yatake, Takuya Katayama
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    UAI
    1997
    113views Artificial Intelligence» more  UAI 1997»
    Structure and Parameter Learning for Causal Independence and Causal Interaction Models
    14 years 11 months ago
    Structure and Parameter Learning for Causal Independence and Causal Interaction Models
    Download  research.microsoft.com
    We begin by discussing causal independence models and generalize these models to causal interaction models. Causal interaction models are models that have independent mechanisms w...
    Christopher Meek, David Heckerman
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    CCR
    2006
    114views more  CCR 2006»
    A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
    14 years 9 months ago
    A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
    Download  ccr.sigcomm.org
    The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
    Nigel Williams, Sebastian Zander, Grenville J. Arm...
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