Online Learning via Global Feedback for Phrase Recognition

  title={Online Learning via Global Feedback for Phrase Recognition},
  author={Xavier Carreras and Llu{\'i}s M{\`a}rquez i Villodre},
This work presents an architecture based on perceptrons to recognize phrase structures, and an online learning algorithm to train the perceptrons together and dependently. The recognition strategy applies learning in two layers: a filtering layer, which reduces the search space by identifying plausible phrase candidates, and a ranking layer, which recursively builds the optimal phrase structure. We provide a recognition-based feedback rule which reflects to each local function its committed… CONTINUE READING
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Discriminative TrainingMethodsfor HiddenMarkov Models : TheoryandExperimentswith PerceptronAlgorithms

  • M. Collins.
  • 2003

Zimak . ConstraintClassificationfor MulticlassClassification andRanking

  • D. Roth S. Har-Peled, andD.
  • 2003

Schapire . Large Margin ClassificationUsing the PerceptronAlgorithm

  • E. Y.FreundandR.
  • MachineLearning
  • 2002

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