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NIPS
2000
15 years 2 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
GECCO
2008
Springer
137views Optimization» more  GECCO 2008»
15 years 1 months ago
Informative sampling for large unbalanced data sets
Selective sampling is a form of active learning which can reduce the cost of training by only drawing informative data points into the training set. This selected training set is ...
Zhenyu Lu, Anand I. Rughani, Bruce I. Tranmer, Jos...
122
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BMCBI
2010
186views more  BMCBI 2010»
15 years 28 days ago
Knowledge-based biomedical word sense disambiguation: comparison of approaches
Background: Word sense disambiguation (WSD) algorithms attempt to select the proper sense of ambiguous terms in text. Resources like the UMLS provide a reference thesaurus to be u...
Antonio Jimeno Yepes, Alan R. Aronson
CIKM
2010
Springer
14 years 11 months ago
Discriminative factored prior models for personalized content-based recommendation
Most existing content-based filtering approaches including Rocchio, Language Models, SVM, Logistic Regression, Neural Networks, etc. learn user profiles independently without ca...
Lanbo Zhang, Yi Zhang 0001
125
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SAC
2010
ACM
14 years 7 months ago
A new methodology for photometric validation in vehicles visual interactive systems
This work proposes a new methodology for automatically validating the internal lighting system of an automotive, i.e., assessing the visual quality of an instrument cluster (IC) f...
Alexandre W. C. Faria, David Menotti, Daniel S. D....