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CORR
2006
Springer
130views Education» more  CORR 2006»
13 years 9 months ago
Genetic Programming for Kernel-based Learning with Co-evolving Subsets Selection
Abstract. Support Vector Machines (SVMs) are well-established Machine Learning (ML) algorithms. They rely on the fact that i) linear learning can be formalized as a well-posed opti...
Christian Gagné, Marc Schoenauer, Mich&egra...
CORR
2006
Springer
104views Education» more  CORR 2006»
13 years 9 months ago
On Universally Decodable Matrices for Space-Time Coding
The notion of universally decodable matrices (UDMs) was recently introduced by Tavildar and Viswanath while studying slow fading channels. It turns out that the problem of construc...
Pascal O. Vontobel, Ashwin Ganesan
IJON
2006
146views more  IJON 2006»
13 years 9 months ago
Feature selection and classification using flexible neural tree
The purpose of this research is to develop effective machine learning or data mining techniques based on flexible neural tree FNT. Based on the pre-defined instruction/operator se...
Yuehui Chen, Ajith Abraham, Bo Yang
JMLR
2008
141views more  JMLR 2008»
13 years 9 months ago
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but oft...
Faustino J. Gomez, Jürgen Schmidhuber, Risto ...
PAMI
2008
391views more  PAMI 2008»
13 years 9 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha