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IJCNN
2007
IEEE
13 years 11 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
ESANN
2006
13 years 6 months ago
LS-SVM functional network for time series prediction
Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
Tuomas Kärnä, Fabrice Rossi, Amaury Lend...
JMLR
2006
186views more  JMLR 2006»
13 years 5 months ago
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples
We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
Mikhail Belkin, Partha Niyogi, Vikas Sindhwani
ICMLA
2009
13 years 3 months ago
Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling
The Mind Speller is a Brain-Computer Interface which enables subjects to spell text on a computer screen by detecting P300 Event-Related Potentials in their electroencephalograms....
Adrien Combaz, Nikolay V. Manyakov, Nikolay Chumer...
JDCTA
2010
104views more  JDCTA 2010»
13 years 2 days ago
Mean Shifts Identification Model in Bivariate Process Based on LS-SVM Pattern Recognizer
This study develops a least squares support vector machines (LS-SVM) based model for bivariate process to diagnose abnormal patterns of process mean vector, and to help identify a...
Zhi-Qiang Cheng, Yi-Zhong Ma, Jing Bu