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  Knockoff Nets: Stealing Functionality of Black-Box Models

Orekondy, T., Schiele, B., & Fritz, M. (2019). Knockoff Nets: Stealing Functionality of Black-Box Models. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4949 -4958). Piscataway, NJ: IEEE. doi:10.1109/CVPR.2019.00509.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0002-AA57-D Version Permalink: https://hdl.handle.net/21.11116/0000-0007-7DB0-6
Genre: Conference Paper
Latex : Knockoff Nets: {S}tealing Functionality of Black-Box Models

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arXiv:1812.02766.pdf (Preprint), 6MB
 
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 Creators:
Orekondy, Tribhuvanesh1, Author           
Schiele, Bernt1, Author           
Fritz, Mario2, Author           
Affiliations:
1Computer Vision and Machine Learning, MPI for Informatics, Max Planck Society, ou_1116547              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 20192019
 Publication Status: Published online
 Pages: 17 p.
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: orekondy18knockoff
DOI: 10.1109/CVPR.2019.00509
 Degree: -

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Title: 32nd IEEE Conference on Computer Vision and Pattern Recognition
Place of Event: Long Beach, CA, USA
Start-/End Date: 2019-06-16 - 2019-06-20

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Title: IEEE/CVF Conference on Computer Vision and Pattern Recognition
  Abbreviation : CVPR 2019
  Subtitle : Proceedings
Source Genre: Proceedings
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Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 4949 - 4958 Identifier: ISBN: 978-1-7281-3293-8