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  Understanding and Controlling Leakage in Machine Learning

Orekondy, T. (2020). Understanding and Controlling Leakage in Machine Learning. PhD Thesis, Universität des Saarlandes, Saarbrücken. doi:10.22028/D291-33551.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0008-4ACC-0 Version Permalink: https://hdl.handle.net/21.11116/0000-0008-4ACD-F
Genre: Thesis

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Locator:
https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/30989 (Any fulltext)
Description:
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OA-Status:
Green

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 Creators:
Orekondy, Tribhuvanesh1, 2, Author           
Schiele, Bernt1, Advisor           
Fritz, Mario3, Referee           
Frahm, Jan-Michael3, Referee
Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2International Max Planck Research School, MPI for Informatics, Max Planck Society, Campus E1 4, 66123 Saarbrücken, DE, ou_1116551              
3External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2020-12-182021-03-302020
 Publication Status: Issued
 Pages: -
 Publishing info: Saarbrücken : Universität des Saarlandes
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Orekondy_PhD2020
DOI: 10.22028/D291-33551
URN: urn:nbn:de:bsz:291--ds-335519
 Degree: PhD

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