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IJON
2011
158views more  IJON 2011»
13 years 3 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
14 years 3 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
14 years 3 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»
13 years 10 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
13 years 10 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