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    » Structured Learning of Component Dependencies in AmI Systems
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    IPPS
    2007
    IEEE
    127views Distributed And Parallel Com...» more  IPPS 2007»
    Experiments with a Software Component Enabling NetSolve with Direct Communications in a Non-Intrusive and Incremental Way
    14 years 1 months ago
    Experiments with a Software Component Enabling NetSolve with Direct Communications in a Non-Intrusive and Incremental Way
    Download  www.cecs.uci.edu
    The paper presents a software component that enables NetSolve with direct communications between servers in a non-intrusive and incremental way. Non-intrusiveness means that the s...
    Xin Zuo, Alexey L. Lastovetsky
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    JMLR
    2006
    113views more  JMLR 2006»
    Learning the Structure of Linear Latent Variable Models
    13 years 7 months ago
    Learning the Structure of Linear Latent Variable Models
    Download  www.hss.cmu.edu
    We describe anytime search procedures that (1) find disjoint subsets of recorded variables for which the members of each subset are d-separated by a single common unrecorded cause...
    Ricardo Silva, Richard Scheines, Clark Glymour, Pe...
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    DATE
    2008
    IEEE
    137views Hardware» more  DATE 2008»
    SPARE - a Scalable algorithm for passive, structure preserving, Parameter-Aware model order REduction
    14 years 2 months ago
    SPARE - a Scalable algorithm for passive, structure preserving, Parameter-Aware model order REduction
    Download  www.date-conference.com
    In this paper we describe a flexible and efficient new algorithm for model order reduction of parameterized systems. The method is based on the reformulation of the parametric s...
    Jorge Fernandez Villena, Luis Miguel Silveira
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    KDD
    2009
    ACM
    172views Data Mining» more  KDD 2009»
    Learning dynamic temporal graphs for oil-production equipment monitoring system
    14 years 6 days ago
    Learning dynamic temporal graphs for oil-production equipment monitoring system
    Download  www-ai.cs.uni-dortmund.de
    Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
    Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
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    ICML
    1996
    IEEE
    153views Machine Learning» more  ICML 1996»
    Learning Relational Concepts with Decision Trees
    14 years 8 months ago
    Learning Relational Concepts with Decision Trees
    Download  www.peter-geibel.de
    In this paper, we describe two di erent learning tasks for relational structures. When learning a classi er for structures, the relational structures in the training sets are clas...
    Peter Geibel, Fritz Wysotzki
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