NLPExplorer

A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping

Michael Bloodgood | K. Vijay-Shanker |

Month: June
Year: 2009
Location: Boulder, Colorado
Venue: CoNLL | WS |
SIG: SIGNLL

Taking into Account the Differences between Actively and Passively Acquired Data: The Case of Active Learning with Support Vector Machines for Imbalanced Datasets
Michael Bloodgood | K. Vijay-Shanker |

Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation
Michael Bloodgood | Chris Callison-Burch |

Using Variance as a Stopping Criterion for Active Learning of Frame Assignment
Masood Ghayoomi |

Analysis of Stopping Active Learning based on Stabilizing Predictions
Michael Bloodgood | John Grothendieck |

Named Entity Recognition

English

The Pragmatics of Referring and the Modality of Communication

Philip R. Cohen |

A computational account of comparative implicatures for a spoken dialogue agent

Luciana Benotti | David Traum |

THE INTONATIONAL STRUCTURING OF DISCOURSE

Julia Hirschberg | Janet Pierrehumbert |

Coordination and context-dependence in the generation of embodied conversation

Justine Cassell | Matthew Stone | Hao Yan |

Gesture Theory is Linguistics: On Modelling Multimodality as Prosody

Dafydd Gibbon |