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Adversarial inter-group link injection degrades the fairness of graph neural networks
Hussain, Hussain
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Cao, Meng
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Sikdar, Sandipan
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Helic, Denis
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Lex, Elisabeth
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Strohmaier, Markus
;
Kern, Roman
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DOI:
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https://doi.org/10.1109/ICDM54844.2022.00117
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URL:
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https://ieeexplore.ieee.org/document/10027598
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Document Type:
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Conference or workshop publication
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Year of publication:
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2022
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Book title:
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2022nd IEEE International Conference on Data Mining : 28 November-1 December 2022, Orlando, Florida : proceedings
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Page range:
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975-980
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Conference title:
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2022 IEEE International Conference on Data Mining (ICDM)
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Location of the conference venue:
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Orlando, FL
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Date of the conference:
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28.11.-01.12.2022
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Publisher:
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Zhu, Xiaodan
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Ranka, Sanjay
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Thai, My T.
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Washio, Takashi
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Wu, Xindong
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Place of publication:
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Los Alamitos, CA [u.a.]
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Publishing house:
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IEEE Computer Society
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ISBN:
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978-1-6654-5099-7
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Related URLs:
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Publication language:
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English
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Institution:
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Business School > Data Science in the Economic and Social Sciences (Strohmaier, 2022-)
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Subject:
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000 Generalities
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Keywords (English):
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fairness , adversarial attacks , graph neural networks
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 | Dieser Eintrag ist Teil der Universitätsbibliographie. |
 Search Authors in
BASE:
Hussain, Hussain
;
Cao, Meng
;
Sikdar, Sandipan
;
Helic, Denis
;
Lex, Elisabeth
;
Strohmaier, Markus
;
Kern, Roman
Google Scholar:
Hussain, Hussain
;
Cao, Meng
;
Sikdar, Sandipan
;
Helic, Denis
;
Lex, Elisabeth
;
Strohmaier, Markus
;
Kern, Roman
ORCID:
Hussain, Hussain ; Cao, Meng ; Sikdar, Sandipan ; Helic, Denis ; Lex, Elisabeth ; Strohmaier, Markus  ORCID: 0000-0002-5485-5720 ; Kern, Roman
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