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ICML
2003
IEEE
16 years 4 months ago
Learning Mixture Models with the Latent Maximum Entropy Principle
We present a new approach to estimating mixture models based on a new inference principle we have proposed: the latent maximum entropy principle (LME). LME is different both from ...
Shaojun Wang, Dale Schuurmans, Fuchun Peng, Yunxin...
BMCBI
2005
153views more  BMCBI 2005»
15 years 3 months ago
Learning Statistical Models for Annotating Proteins with Function Information using Biomedical Text
Background: The BioCreative text mining evaluation investigated the application of text mining methods to the task of automatically extracting information from text in biomedical ...
Soumya Ray, Mark Craven
131
Voted
NAACL
2010
15 years 1 months ago
Minimally-Supervised Extraction of Entities from Text Advertisements
Extraction of entities from ad creatives is an important problem that can benefit many computational advertising tasks. Supervised and semi-supervised solutions rely on labeled da...
Sameer Singh, Dustin Hillard, Chris Leggetter
ISVC
2010
Springer
15 years 2 months ago
Automatic Learning of Gesture Recognition Model Using SOM and SVM
In this paper, we propose an automatic learning method for gesture recognition. We combine two different pattern recognition techniques: the SelfOrganizing Map (SOM) and Support Ve...
Masaki Oshita, Takefumi Matsunaga
MLMI
2007
Springer
15 years 10 months ago
Meeting State Recognition from Visual and Aural Labels
In this paper we present a meeting state recognizer based on a combination of multi-modal sensor data in a smart room. Our approach is based on the training of a statistical model ...
Jan Curín, Pascal Fleury, Jan Kleindienst, ...