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» Geometric Neural Networks and Support Multi-Vector Machines
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IJCNN
2006
IEEE
14 years 1 months ago
Semi-Supervised Model Selection Based on Cross-Validation
We propose a new semi-supervised model selection method that is derived by applying the structural risk minimization principle to a recent semi-supervised generalization error bou...
Matti Kaariainen
ICIAP
2003
ACM
14 years 18 days ago
PCA vs low resolution images in face verification
Principal Components Analysis (PCA) has been one of the most applied methods for face verification using only 2D information, in fact, PCA is practically the method of choice for ...
Cristina Conde, Antonio Ruiz, Enrique Cabello
HAIS
2009
Springer
14 years 20 hour ago
Pareto-Based Multi-output Model Type Selection
In engineering design the use of approximation models (= surrogate models) has become standard practice for design space exploration, sensitivity analysis, visualization and optimi...
Dirk Gorissen, Ivo Couckuyt, Karel Crombecq, Tom D...
CEC
2008
IEEE
14 years 1 months ago
Automatic model type selection with heterogeneous evolution: An application to RF circuit block modeling
— Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a cost effe...
Dirk Gorissen, Luciano De Tommasi, Jeroen Croon, T...
ICDM
2007
IEEE
97views Data Mining» more  ICDM 2007»
14 years 1 months ago
Supervised Learning by Training on Aggregate Outputs
Supervised learning is a classic data mining problem where one wishes to be be able to predict an output value associated with a particular input vector. We present a new twist on...
David R. Musicant, Janara M. Christensen, Jamie F....