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» Approximation Methods for Supervised Learning
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DEXA
2008
Springer
123views Database» more  DEXA 2008»
13 years 12 months ago
Evolutionary Clustering in Description Logics: Controlling Concept Formation and Drift in Ontologies
Abstract. We present a method based on clustering techniques to detect concept drift or novelty in a knowledge base expressed in Description Logics. The method exploits an effectiv...
Nicola Fanizzi, Claudia d'Amato, Floriana Esposito
BIOINFORMATICS
2005
140views more  BIOINFORMATICS 2005»
13 years 10 months ago
Profile-based direct kernels for remote homology detection and fold recognition
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...
Huzefa Rangwala, George Karypis
GECCO
2007
Springer
558views Optimization» more  GECCO 2007»
14 years 4 months ago
A chain-model genetic algorithm for Bayesian network structure learning
Bayesian Networks are today used in various fields and domains due to their inherent ability to deal with uncertainty. Learning Bayesian Networks, however is an NP-Hard task [7]....
Ratiba Kabli, Frank Herrmann, John McCall
CGF
2005
252views more  CGF 2005»
13 years 10 months ago
Support Vector Machines for 3D Shape Processing
We propose statistical learning methods for approximating implicit surfaces and computing dense 3D deformation fields. Our approach is based on Support Vector (SV) Machines, which...
Florian Steinke, Bernhard Schölkopf, Volker B...
LION
2009
Springer
152views Optimization» more  LION 2009»
14 years 4 months ago
Comparison of Coarsening Schemes for Multilevel Graph Partitioning
Graph partitioning is a well-known optimization problem of great interest in theoretical and applied studies. Since the 1990s, many multilevel schemes have been introduced as a pra...
Cédric Chevalier, Ilya Safro