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ICPR
2000
IEEE
14 years 8 months ago
Data Condensation in Large Databases by Incremental Learning with Support Vector Machines
An algorithmfor data condensation using support vector machines (SVM's)is presented. The algorithm extracts datapoints lying close to the class boundaries,whichform a much re...
Pabitra Mitra, C. A. Murthy, Sankar K. Pal
PKDD
2009
Springer
174views Data Mining» more  PKDD 2009»
14 years 2 months ago
Active and Semi-supervised Data Domain Description
Data domain description techniques aim at deriving concise descriptions of objects belonging to a category of interest. For instance, the support vector domain description (SVDD) l...
Nico Görnitz, Marius Kloft, Ulf Brefeld
JUCS
2008
147views more  JUCS 2008»
13 years 7 months ago
Authoring Courses with Rich Adaptive Sequencing for IMS Learning Design
: This paper describes the process of translating an adaptive sequencing strategy designed using Sequencing Graphs to the semantics of IMS Learning Design. The relevance of this co...
Sergio Gutiérrez Santos, Abelardo Pardo, Ca...
ACL
2006
13 years 9 months ago
Learning Transliteration Lexicons from the Web
This paper presents an adaptive learning framework for Phonetic Similarity Modeling (PSM) that supports the automatic construction of transliteration lexicons. The learning algori...
Jin-Shea Kuo, Haizhou Li, Ying-Kuei Yang
ESANN
2003
13 years 9 months ago
Approximation of Function by Adaptively Growing Radial Basis Function Neural Networks
In this paper a neural network for approximating function is described. The activation functions of the hidden nodes are the Radial Basis Functions (RBF) whose parameters are learn...
Jianyu Li, Siwei Luo, Yingjian Qi