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IJON
2011
158views more  IJON 2011»
14 years 11 months ago
Maximal Discrepancy for Support Vector Machines
Several theoretical methods have been developed in the past years to evaluate the generalization ability of a classifier: they provide extremely useful insights on the learning ph...
Davide Anguita, Alessandro Ghio, Sandro Ridella
IJCNN
2006
IEEE
15 years 10 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
ICALT
2007
IEEE
15 years 10 months ago
The PLExus Prototype: A PLE realized as Topic Maps
The article presents the PLExus prototype, a Personal Learning Environment based on the semantic technology of topic maps. Semantic-based navigation in e-learning will enable vari...
Line Kolås, Arvid Staupe
LREC
2008
104views Education» more  LREC 2008»
15 years 5 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...
AAAI
1998
15 years 5 months ago
Machine Learning of Generic and User-Focused Summarization
A key problem in text summarization is finding a salience function which determines what information in the source should be included in the summary. This paper describes the use ...
Inderjeet Mani, Eric Bloedorn