Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Sergei V. Pereverzyev"'
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 5 (2019)
This paper deals with the problem of semi-supervised learning using a small number of training samples. Traditional kernel based methods utilize either a fixed kernel or a combination of judiciously chosen kernels from a fixed dictionary. In contrast
Externí odkaz:
https://doaj.org/article/852c29af640948ecbccd24e5acbd8fe9
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 3 (2017)
We consider the question of 30-min prediction of blood glucose levels measured by continuous glucose monitoring devices, using clinical data. While most studies of this nature deal with one patient at a time, we take a certain percentage of patients
Externí odkaz:
https://doaj.org/article/45882753c0c34fd5aad60ee7a3a0bc5a
Autor:
Elke R. Gizewski, Lukas Mayer, Bernhard A. Moser, Duc Hoan Nguyen, Sergiy Pereverzyev, Sergei V. Pereverzyev, Natalia Shepeleva, Werner Zellinger
Publikováno v:
Applied and Computational Harmonic Analysis. 57:201-227
Publikováno v:
Fractional Calculus and Applied Analysis. 23:694-722
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 7 (2021)
The problem of real time prediction of blood glucose (BG) levels based on the readings from a continuous glucose monitoring (CGM) device is a problem of great importance in diabetes care, and therefore, has attracted a lot of research in recent years
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5134f00b3c483c309f8fcdb8ac060223
Publikováno v:
2018 MATRIX Annals ISBN: 9783030382292
This paper is an announcement for our longer paper in preparation. Traditional kernel based methods utilize either a fixed kernel or a combination of judiciously chosen kernels from a fixed dictionary. In contrast, we construct a data-dependent kerne
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3571d4e9022057537acda1cec786d2b
https://doi.org/10.1007/978-3-030-38230-8_8
https://doi.org/10.1007/978-3-030-38230-8_8
Publikováno v:
Springer Proceedings in Mathematics & Statistics ISBN: 9789811515910
For \(\nu \in (0,1)\), we analyze the semilinear integro-differential equation on the multidimensional space domain Open image in new window in the unknown \(u=u(x,t)\): $$\mathbf {D}_{t}^{\nu }u-\mathcal {L}_{1}u-\int _{0}^{t}\mathcal {K}(t-s)\mathc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e9c591a325cb03f5dd2feab8100c178b
https://doi.org/10.1007/978-981-15-1592-7_10
https://doi.org/10.1007/978-981-15-1592-7_10
Publikováno v:
Processes
Volume 9
Issue 1
Processes, Vol 9, Iss 108, p 108 (2021)
Volume 9
Issue 1
Processes, Vol 9, Iss 108, p 108 (2021)
Identification of ongoing processes in solid oxide fuel cells (SOFC) enables both optimizing the operating environment and prolonging the lifetime of SOFC. The Levenberg&ndash
Marquardt algorithm (LMA) is commonly used in the characterization of
Marquardt algorithm (LMA) is commonly used in the characterization of
Publikováno v:
Journal of Complexity. 33:14-29
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 gives a better
Autor:
Pavlo Tkachenko, Sergei V. Pereverzyev
Publikováno v:
Computational Methods in Applied Mathematics. 15:213-219
In the present paper, we consider the approximation of the solution of an ill-posed spherical pseudo-differential equation at a given point. While the methods for approximating the whole solution are well-studied in Hilbert spaces, such as the space