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ICIP
2006
IEEE
16 years 1 months ago
Precision-Oriented Active Selection for Interactive Image Retrieval
Active learning methods have been considered with an increased interest in the content-based image retrieval (CBIR) community. Those methods used to be based on classical classifi...
Philippe Henri Gosselin, Matthieu Cord
ECML
2005
Springer
15 years 5 months ago
Active Learning for Probability Estimation Using Jensen-Shannon Divergence
Active selection of good training examples is an important approach to reducing data-collection costs in machine learning; however, most existing methods focus on maximizing classi...
Prem Melville, Stewart M. Yang, Maytal Saar-Tsecha...
TLT
2008
93views more  TLT 2008»
14 years 11 months ago
What Do You Prefer? Using Preferences to Enhance Learning Technology
While the growing number of learning resources increases the choice for learners on how, what and when to learn, it also makes it more and more difficult to find the learning resou...
Philipp Kärger, Daniel Olmedilla, Fabian Abel...
IJAR
2010
97views more  IJAR 2010»
14 years 10 months ago
Parameter estimation and model selection for mixtures of truncated exponentials
Bayesian networks with mixtures of truncated exponentials (MTEs) support efficient inference algorithms and provide a flexible way of modeling hybrid domains (domains containing ...
Helge Langseth, Thomas D. Nielsen, Rafael Rum&iacu...
GECCO
2008
Springer
232views Optimization» more  GECCO 2008»
15 years 26 days ago
An efficient SVM-GA feature selection model for large healthcare databases
This paper presents an efficient hybrid feature selection model based on Support Vector Machine (SVM) and Genetic Algorithm (GA) for large healthcare databases. Even though SVM an...
Rick Chow, Wei Zhong, Michael Blackmon, Richard St...