A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
A Generalized Representer Theorem
COLT '01/EuroCOLT '01 Proceedings of the 14th Annual Conference on Computational Learning Theory and and 5th European Conference on Computational Learning Theory
Learning Eigenfunctions Links Spectral Embedding and Kernel PCA
Neural Computation
Functional Learning of Kernels for Information Fusion Purposes
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Representing Functional Data Using Support Vector Machines
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Functional Data Analysis with R and MATLAB
Functional Data Analysis with R and MATLAB
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We afford the classification of time series in the Functional Data Analysis (FDA) context. To this aim we introduce projections methods for the time series onto appropriate Reproducing Kernel Hilbert Spaces (RKHSs) with the aid of Regularization Theory. Next we project the curves onto a set of different RKHSs. Then we consider the induced Euclidean metrics in these spaces and combine them in order to obtain a single kernel valid for classification purposes. The methodology is tested on some real and simulated classification examples.