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    » A Neural Probabilistic Language Model
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    EACL
    2006
    ACL Anthology
    91views Natural Language Processing» more  EACL 2006»
    A Probabilistic Answer Type Model
    14 years 11 months ago
    A Probabilistic Answer Type Model
    Download  acl.ldc.upenn.edu
    All questions are implicitly associated with an expected answer type. Unlike previous approaches that require a predefined set of question types, we present a method for dynamical...
    Christopher Pinchak, Dekang Lin
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    ESANN
    2008
    118views Neural Networks» more  ESANN 2008»
    Word recognition and incremental learning based on neural associative memories and hidden Markov models
    14 years 11 months ago
    Word recognition and incremental learning based on neural associative memories and hidden Markov models
    Download  www.dice.ucl.ac.be
    Abstract. An architecture for achieving word recognition and incremental learning of new words in a language processing system is presented. The architecture is based on neural ass...
    Zöhre Kara Kayikci, Günther Palm
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    ICML
    2005
    IEEE
    97views Machine Learning» more  ICML 2005»
    Learning to rank using gradient descent
    15 years 10 months ago
    Learning to rank using gradient descent
    Download  www.machinelearning.org
    We investigate using gradient descent methods for learning ranking functions; we propose a simple probabilistic cost function, and we introduce RankNet, an implementation of these...
    Christopher J. C. Burges, Tal Shaked, Erin Renshaw...
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    COGSCI
    2010
    125views more  COGSCI 2010»
    A Probabilistic Computational Model of Cross-Situational Word Learning
    14 years 9 months ago
    A Probabilistic Computational Model of Cross-Situational Word Learning
    Download  www.coli.uni-saarland.de
    Words are the essence of communication: they are the building blocks of any language. Learning the meaning of words is thus one of the most important aspects of language acquisiti...
    Afsaneh Fazly, Afra Alishahi, Suzanne Stevenson
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    ISAMI
    2010
    119views Emerging Technology» more  ISAMI 2010»
    Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy
    14 years 7 months ago
    Employing Compact Intra-genomic Language Models to Predict Genomic Sequences and Characterize Their Entropy
    Download  marco.uminho.pt
    Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
    Sérgio A. D. Deusdado, Paulo Carvalho
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