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ICML
2005
IEEE
14 years 11 months ago
Active learning for Hidden Markov Models: objective functions and algorithms
Hidden Markov Models (HMMs) model sequential data in many fields such as text/speech processing and biosignal analysis. Active learning algorithms learn faster and/or better by cl...
Brigham Anderson, Andrew Moore
ICML
2005
IEEE
14 years 11 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
ICML
2005
IEEE
14 years 11 months ago
Learning discontinuities with products-of-sigmoids for switching between local models
Sensorimotor data from many interesting physical interactions comprises discontinuities. While existing locally weighted learning approaches aim at learning smooth functions, we p...
Marc Toussaint, Sethu Vijayakumar
ICML
1998
IEEE
14 years 11 months ago
Employing EM and Pool-Based Active Learning for Text Classification
This paper shows how a text classifier's need for labeled training documents can be reduced by taking advantage of a large pool of unlabeled documents. We modify the Query-by...
Andrew McCallum, Kamal Nigam
ALT
2006
Springer
14 years 7 months ago
Towards a Better Understanding of Incremental Learning
Abstract. The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requi...
Sanjay Jain, Steffen Lange, Sandra Zilles