Now showing items 1-6 of 6

  • An empirical study of semi-supervised structured conditional models for dependency parsing 

    Suzuki, Jun; Isozaki, Hideki; Carreras Pérez, Xavier; Collins, Michael (2009)
    Conference report
    Open Access
    This paper describes an empirical study of high-performance dependency parsers based on a semi-supervised learning approach. We describe an extension of semisupervised structured conditional models (SS-SCMs) to the dependency ...
  • Exponentiated gradient algorithms for conditional random fields and max-margin Markov networks 

    Collins, Michael; Globerson, Amir; Koo, Terry; Carreras Pérez, Xavier; Bartlett, Peter (2008-08)
    Article
    Open Access
    Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore ...
  • Non-projective parsing for statistical machine translation 

    Carreras Pérez, Xavier; Collins, Michael (2009)
    Conference report
    Open Access
    We describe a novel approach for syntaxbased statistical MT, which builds on a variant of tree adjoining grammar (TAG). Inspired by work in discriminative dependency parsing, the key idea in our approach is to allow highly ...
  • Simple semi-supervised dependency parsing 

    Koo, Terry; Carreras Pérez, Xavier; Collins, Michael (2008)
    Conference report
    Open Access
    We present a simple and effective semisupervised method for training dependency parsers. We focus on the problem of lexical representation, introducing features that incorporate word clusters derived from a large unannotated ...
  • Structured prediction models via the matrix-tree theorem 

    Koo, Terry; Globerson, Amir; Carreras Pérez, Xavier; Collins, Michael (2007)
    Conference report
    Open Access
    This paper provides an algorithmic framework for learning statistical models involving directed spanning trees, or equivalently non-projective dependency structures. We show how partition functions and marginals for directed ...
  • TAG, dynamic programming, and the perceptron for efficient, feature-rich parsing 

    Carreras Pérez, Xavier; Collins, Michael; Koo, Terry (Coling 2008 Organizing Committee, 2008)
    Conference report
    Open Access
    We describe a parsing approach that makes use of the perceptron algorithm, in conjunction with dynamic programming methods, to recover full constituent-based parse trees. The formalism allows a rich set of parse-tree ...