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» Kernel Machines and Boolean Functions
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TKDE
2002
133views more  TKDE 2002»
13 years 7 months ago
Binary Rule Generation via Hamming Clustering
The generation of a set of rules underlying a classification problem is performed by applying a new algorithm, called Hamming Clustering (HC). It reconstructs the and-or expressio...
Marco Muselli, Diego Liberati
FOCS
1990
IEEE
13 years 11 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Avrim Blum
JMLR
2006
143views more  JMLR 2006»
13 years 7 months ago
Consistency and Convergence Rates of One-Class SVMs and Related Algorithms
We determine the asymptotic behaviour of the function computed by support vector machines (SVM) and related algorithms that minimize a regularized empirical convex loss function i...
Régis Vert, Jean-Philippe Vert
JMLR
2006
150views more  JMLR 2006»
13 years 7 months ago
Building Support Vector Machines with Reduced Classifier Complexity
Support vector machines (SVMs), though accurate, are not preferred in applications requiring great classification speed, due to the number of support vectors being large. To overc...
S. Sathiya Keerthi, Olivier Chapelle, Dennis DeCos...
KES
2007
Springer
14 years 1 months ago
Inductive Concept Retrieval and Query Answering with Semantic Knowledge Bases Through Kernel Methods
This work deals with the application of kernel methods to structured relational settings such as semantic knowledge bases expressed in Description Logics. Our method integrates a n...
Nicola Fanizzi, Claudia d'Amato