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    ML
    2006
    ACM
    122views Machine Learning» more  ML 2006»
    PRL: A probabilistic relational language
    14 years 9 months ago
    PRL: A probabilistic relational language
    Download  linqs.cs.umd.edu
    In this paper, we describe the syntax and semantics for a probabilistic relational language (PRL). PRL is a recasting of recent work in Probabilistic Relational Models (PRMs) into ...
    Lise Getoor, John Grant
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    NN
    2007
    Springer
    91views Neural Networks» more  NN 2007»
    Edge of chaos and prediction of computational performance for neural circuit models
    14 years 9 months ago
    Edge of chaos and prediction of computational performance for neural circuit models
    Download  www.igi.tugraz.at
    We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We ...
    Robert A. Legenstein, Wolfgang Maass
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    DKE
    2000
    102views more  DKE 2000»
    A Generic Framework for the Modeling of Contexts and its Applications
    14 years 9 months ago
    A Generic Framework for the Modeling of Contexts and its Applications
    Download  www.pri.univie.ac.at
    : Large information bases that are used by several different users and applications accommodate the demands of their users more effectively, if they can be split into possibly over...
    Renate Motschnig-Pitrik
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    PR
    2007
    104views more  PR 2007»
    Optimizing resources in model selection for support vector machine
    14 years 9 months ago
    Optimizing resources in model selection for support vector machine
    Download  www.livia.etsmtl.ca
    Tuning SVM hyperparameters is an important step in achieving a high-performance learning machine. It is usually done by minimizing an estimate of generalization error based on the...
    Mathias M. Adankon, Mohamed Cheriet
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    ICML
    2007
    IEEE
    142views Machine Learning» more  ICML 2007»
    Discriminative learning for differing training and test distributions
    15 years 10 months ago
    Discriminative learning for differing training and test distributions
    Download  www.mpi-inf.mpg.de
    We address classification problems for which the training instances are governed by a distribution that is allowed to differ arbitrarily from the test distribution--problems also ...
    Michael Brückner, Steffen Bickel, Tobias Sche...
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