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» Improving Language Models by Clustering Training Sentences
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EMNLP
2011
12 years 7 months ago
Training a Log-Linear Parser with Loss Functions via Softmax-Margin
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...
Michael Auli, Adam Lopez
ISBI
2004
IEEE
14 years 8 months ago
Clustering On Image Boundary Regions for Deformable Model Segmentation
We present a novel approach, clustering on local image profiles, for statistically characterizing image intensity in object boundary regions. In deformable model segmentation, a d...
Joshua Stough, Stephen M. Pizer, Edward L. Chaney,...
EMNLP
2009
13 years 5 months ago
Parser Adaptation and Projection with Quasi-Synchronous Grammar Features
We connect two scenarios in structured learning: adapting a parser trained on one corpus to another annotation style, and projecting syntactic annotations from one language to ano...
David A. Smith, Jason Eisner
LREC
2010
146views Education» more  LREC 2010»
13 years 9 months ago
Online Temporal Language Model Adaptation for a Thai Broadcast News Transcription System
This paper investigates the effectiveness of online temporal language model adaptation when applied to a Thai broadcast news transcription task. Our adaptation scheme works as fol...
Kwanchiva Saykham, Ananlada Chotimongkol, Chai Wut...
IR
2010
13 years 5 months ago
Sentence-level event classification in unstructured texts
The ability to correctly classify sentences that describe events is an important task for many natural language applications such as Question Answering (QA) and Text Summarisation....
Martina Naughton, Nicola Stokes, Joe Carthy