35 search results - page 3 / 7 » Transfer Learning, Feature Selection and Word Sense Disambig... |
JMLR
2011
13 years 18 days ago
2011
We propose a framework MIC (Multiple Inclusion Criterion) for learning sparse models based on the information theoretic Minimum Description Length (MDL) principle. MIC provides an...
COLING
2002
13 years 5 months ago
2002
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
FGCN
2008
IEEE
14 years 2 days ago
2008
IEEE
Word sense disambiguation has always been a key problem in Natural Language Processing. In the paper, we use the method of Information Gain to calculate the weight of different po...
JMLR
2010
13 years 12 days ago
2010
Feature selection for supervised learning can be greatly improved by making use of the fact that features often come in classes. For example, in gene expression data, the genes wh...
ECAI
2000
Springer
13 years 10 months ago
2000
Springer
Abstract. This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar–basedclassification, on the Word Sens...