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    EMNLP
    2006
    99views Natural Language Processing» more  EMNLP 2006»
    Domain Adaptation with Structural Correspondence Learning
    14 years 11 months ago
    Domain Adaptation with Structural Correspondence Learning
    Download  john.blitzer.com
    Discriminative learning methods are widely used in natural language processing. These methods work best when their training and test data are drawn from the same distribution. For...
    John Blitzer, Ryan T. McDonald, Fernando Pereira
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    IJCAI
    2003
    106views Artificial Intelligence» more  IJCAI 2003»
    Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference
    14 years 11 months ago
    Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference
    Download  www.cs.umass.edu
    Coreference analysis, also known as record linkage or identity uncertainty, is a difficult and important problem in natural language processing, databases, citation matching and ...
    Andrew McCallum, Ben Wellner
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    EMNLP
    2007
    144views Natural Language Processing» more  EMNLP 2007»
    Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model
    14 years 11 months ago
    Fast and Robust Multilingual Dependency Parsing with a Generative Latent Variable Model
    Download  cui.unige.ch
    We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
    Ivan Titov, James Henderson
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    EMNLP
    2007
    102views Natural Language Processing» more  EMNLP 2007»
    Probabilistic Models of Nonprojective Dependency Trees
    14 years 11 months ago
    Probabilistic Models of Nonprojective Dependency Trees
    Download  www.cs.cmu.edu
    A notable gap in research on statistical dependency parsing is a proper conditional probability distribution over nonprojective dependency trees for a given sentence. We exploit t...
    David A. Smith, Noah A. Smith
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    JMLR
    2012
    181views Programming Languages» more  JMLR 2012»
    On Nonparametric Guidance for Learning Autoencoder Representations
    12 years 12 months ago
    On Nonparametric Guidance for Learning Autoencoder Representations
    Download  www.dmi.usherb.ca
    Unsupervised discovery of latent representations, in addition to being useful for density modeling, visualisation and exploratory data analysis, is also increasingly important for...
    Jasper Snoek, Ryan Prescott Adams, Hugo Larochelle
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