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We present a support vector machines (SVM) rationale suitable for regression and quaternary classification problems that use complex data, exploiting the notions of widely linear estimation and pure c...
We investigate the relation of two fundamental tools in machine learning, that is the support vector machine (SVM) for classification, and the Lasso technique used in regression. We show that the resu...
In nonparametric classification and regression problems, support vector machines (SVMs) attract much attention in theoretical and in applied statistics. In an abstract sense, SVMs can be seen as regu...
When applying the support vector machine (SVM) to high-dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The ...
We consider the problem of forecasting the next (observable) state of an unknown ergodic dynamical system from a noisy observation of the present state. Our main result shows, for example, that sup...

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