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» Support Vector Machines: Theory and Applications
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KES
2008
Springer
14 years 11 months ago
Classification and Retrieval through Semantic Kernels
Abstract. This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting wellfounded kernel methods fo...
Claudia d'Amato, Nicola Fanizzi, Floriana Esposito
SEMWEB
2010
Springer
14 years 9 months ago
Supporting Natural Language Processing with Background Knowledge: Coreference Resolution Case
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Volha Bryl, Claudio Giuliano, Luciano Serafini, Ka...
ICML
2007
IEEE
16 years 19 days ago
Local similarity discriminant analysis
We propose a local, generative model for similarity-based classification. The method is applicable to the case that only pairwise similarities between samples are available. The c...
Luca Cazzanti, Maya R. Gupta
ICML
2008
IEEE
16 years 19 days ago
A dual coordinate descent method for large-scale linear SVM
In many applications, data appear with a huge number of instances as well as features. Linear Support Vector Machines (SVM) is one of the most popular tools to deal with such larg...
Cho-Jui Hsieh, Kai-Wei Chang, Chih-Jen Lin, S. Sat...
COLT
2001
Springer
15 years 4 months ago
Rademacher and Gaussian Complexities: Risk Bounds and Structural Results
We investigate the use of certain data-dependent estimates of the complexity of a function class, called Rademacher and Gaussian complexities. In a decision theoretic setting, we ...
Peter L. Bartlett, Shahar Mendelson