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» Learning Rules to Improve a Machine Translation System
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NIPS
2007
15 years 5 months ago
HM-BiTAM: Bilingual Topic Exploration, Word Alignment, and Translation
We present a novel paradigm for statistical machine translation (SMT), based on a joint modeling of word alignment and the topical aspects underlying bilingual document-pairs, via...
Bing Zhao, Eric P. Xing
CIBCB
2009
IEEE
15 years 5 months ago
Application of machine learning approaches on quantitative structure activity relationships
Machine Learning techniques are successfully applied to establish quantitative relations between chemical structure and biological activity (QSAR), i.e. classify compounds as activ...
Mariusz Butkiewicz, Ralf Mueller, Danilo Selic, Er...
AAI
2008
93views more  AAI 2008»
15 years 4 months ago
Adaptive Machine Learning in Delayed Feedback Domains by Selective Relearning
We present a novel hybrid technique for improving the predictive performance of an online Machine Learning system: Combining advantages from both memory based and concept based pr...
Marcus-Christopher Ludl, Achim Lewandowski, Georg ...
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IJON
2006
134views more  IJON 2006»
15 years 3 months ago
A new approach to fuzzy classifier systems and its application in self-generating neuro-fuzzy systems
A classifier system is a machine learning system that learns syntactically simple string rules (called classifiers) through a genetic algorithm to guide its performance in an arbi...
Mu-Chun Su, Chien-Hsing Chou, Eugene Lai, Jonathan...
ACL
2011
14 years 7 months ago
Rare Word Translation Extraction from Aligned Comparable Documents
We present a first known result of high precision rare word bilingual extraction from comparable corpora, using aligned comparable documents and supervised classification. We in...
Emmanuel Prochasson, Pascale Fung