Pavlo Tkachenko

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Parameter choice strategies for least-squares approximation of noisy smooth functions on the sphere Powered by TCPDF ( Abstract. We consider a polynomial reconstruction of smooth functions from their noisy values at discrete nodes on the unit sphere by a variant of the regularized least-squares method of An et al. As nodes we use the points of(More)
Regularization schemes are frequently used for performing ranking tasks. This topic has been intensively studied in recent years. However, to be effective a regularization scheme should be equipped with a suitable strategy for choosing a regularization parameter. In the present study we discuss an approach, which is based on the idea of a linear combination(More)
On the convergence rate and some applications of regularized ranking algorithms Powered by TCPDF ( Abstract This paper studies the ranking problem in the context of the regularization theory that allows a simultaneous analysis of a wide class of ranking algorithms. Some of them were previously studied separately. For such ones, our analysis(More)
BACKGROUND AND OBJECTIVE Nocturnal hypoglycemia (NH) is common in patients with insulin-treated diabetes. Despite the risk associated with NH, there are only a few methods aiming at the prediction of such events based on intermittent blood glucose monitoring data and none has been validated for clinical use. Here we propose a method of combining several(More)
Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions Powered by TCPDF ( manuscript No. Abstract In this paper, a two-step regularization method is used to solve an ill-posed spherical pseudo-differential equation in the presence of noisy data. For the first step of(More)
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