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» Language model adaptation using Random Forests
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CSDA
2008
128views more  CSDA 2008»
13 years 7 months ago
Classification tree analysis using TARGET
Tree models are valuable tools for predictive modeling and data mining. Traditional tree-growing methodologies such as CART are known to suffer from problems including greediness,...
J. Brian Gray, Guangzhe Fan
ICCPOL
2009
Springer
13 years 5 months ago
A Simple and Efficient Model Pruning Method for Conditional Random Fields
Conditional random fields (CRFs) have been quite successful in various machine learning tasks. However, as larger and larger data become acceptable for the current computational ma...
Hai Zhao, Chunyu Kit
LREC
2010
169views Education» more  LREC 2010»
13 years 9 months ago
Using Comparable Corpora to Adapt a Translation Model to Domains
Statistical machine translation (SMT) requires a large parallel corpus, which is available only for restricted language pairs and domains. To expand the language pairs and domains...
Hiroyuki Kaji, Takashi Tsunakawa, Daisuke Okada
EUROPAR
2005
Springer
14 years 1 months ago
A Generic Language for Dynamic Adaptation
Today, component oriented middlewares are used to design, develop and deploy distributed applications easily. They ensure the heterogeneity, interoperability, and reuse of software...
Assia Hachichi, Gaël Thomas, Cyril Martin, Be...
WWW
2005
ACM
14 years 8 months ago
Building adaptable and reusable XML applications with model transformations
We present an approach in which the semantics of an XML language is defined by means of a transformation from an XML document model (an XML schema) to an application specific mode...
Ivan Kurtev, Klaas van den Berg