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Collections :	Ιδρυματικό Αποθετήριο ΟΠΑ / AUEB Institutional Repository Σχολή Επιστημών και Τεχνολογίας της Πληροφορίας / School of Informatics Τμήμα Στατιστικής / Department of Statistics Μεταπτυχιακές Εργασίες / Postgraduate dissertations

Title :	Reprodusing Kernel Hilbert spaces and their applications in probability and statistics

Alternative Title :	Χώροι Hilbert με αναπαραγωγικό πυρήνα και εφαρμογές τους στην στατιστική και στις πιθανότητες

Creator :	Dristellas, Demetrios

Contributor :	Giannakopoulos, A. (Επιβλέπων καθηγητής) Athens University of Economics and Business, Department of Statistics (Degree granting institution)

Type :	Text

Extent :	96 σ.

Language :	en

Abstract :	In a large variety of problems in Statistics and Stochastic processes, the random variables which are used do not present finite dimensionality, in contrary their dimension is infinite. On the other hand, the observations of those random variables are actually finitedimensional approximations of corresponding infinite dimensional subjects. Reproducing Kernel Hilbert Spaces (RKHS) are a useful theoretical and practical tool which provides us a series useful representations even for non-linear data. This work will be an introduction to the theory of RKHS in the context of the smoothness of a data set.

Abstract :

In a large variety of problems in Statistics and Stochastic processes, the random variables which are used do not present finite dimensionality, in contrary their dimension is infinite. On the other hand, the observations of those random variables are actually finitedimensional approximations of corresponding infinite dimensional subjects. Reproducing Kernel Hilbert Spaces (RKHS) are a useful theoretical and practical tool which provides us a series useful representations even for non-linear data. This work will be an introduction to the theory of RKHS in the context of the smoothness of a data set.

Subject :	Random variables Kernel Hilbert spaces (RKHS) Non-linear model Probability

Date Issued :	22-07-2015

Licence :

File: Dristellas_2015.pdf

Type: application/pdf

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