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On extension theorems and their connection to universal consistency in machine learning

Title data

Christmann, Andreas ; Dumpert, Florian ; Xiang, Dao-Hong:
On extension theorems and their connection to universal consistency in machine learning.
In: Analysis and Applications. Vol. 14 (2016) Issue 6 . - pp. 795-808.
ISSN 0219-5305
DOI: https://doi.org/10.1142/S0219530516400029

Further data

Item Type: Article in a journal
Refereed: Yes
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics VII - Stochastics and Machine Learning > Chair Mathematics VII - Stochastics and mashine learning - Univ.-Prof. Dr. Andreas Christmann
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics VII - Stochastics and Machine Learning
Result of work at the UBT: Yes
DDC Subjects: 500 Science > 510 Mathematics
Date Deposited: 31 Oct 2016 10:09
Last Modified: 07 Aug 2023 13:13
URI: https://eref.uni-bayreuth.de/id/eprint/35027