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    DAGSTUHL
    2007
    110views Software Engineering» more  DAGSTUHL 2007»
    Two-Dimensional Belief Change
    13 years 11 months ago
    Two-Dimensional Belief Change
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    ABSTRACT: In this paper I present the model of ‘bounded revision’ that is based on two-dimensional revision functions taking as arguments pairs consisting of an input sentence ...
    Hans Rott
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    ESANN
    2007
    134views Neural Networks» more  ESANN 2007»
    Classifying n-back EEG data using entropy and mutual information features
    13 years 11 months ago
    Classifying n-back EEG data using entropy and mutual information features
    Download  www.physics.brown.edu
    In this work we show that entropy (H) and mutual information (MI) can be used as methods for extracting spatially localized features for classification purposes. In order to incre...
    Liang Wu, Predrag Neskovic, Etienne Reyes, Elena F...
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    EUSFLAT
    2007
    193views Fuzzy Logic» more  EUSFLAT 2007»
    A Universal Integral
    13 years 11 months ago
    A Universal Integral
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    Based on a minimal set of axioms we introduce a general integral which can be defined on arbitrary measurable spaces. It acts on measures which are only (finite) monotone set fu...
    Erich-Peter Klement, Radko Mesiar, Endre Pap
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    ICONIP
    2007
    131views Information Technology» more  ICONIP 2007»
    Analysis on Bidirectional Associative Memories with Multiplicative Weight Noise
    13 years 11 months ago
    Analysis on Bidirectional Associative Memories with Multiplicative Weight Noise
    Download  web.nchu.edu.tw
    Abstract. In neural networks, network faults can be exhibited in different forms, such as node fault and weight fault. One kind of weight faults is due to the hardware or software ...
    Chi-Sing Leung, Pui-Fai Sum, Tien-Tsin Wong
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    IJCAI
    2007
    169views Artificial Intelligence» more  IJCAI 2007»
    Improving Embeddings by Flexible Exploitation of Side Information
    13 years 11 months ago
    Improving Embeddings by Flexible Exploitation of Side Information
    Download  www.ijcai.org
    Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
    Ali Ghodsi, Dana F. Wilkinson, Finnegan Southey
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