A survey on Adversarial Recommender Systems: from Attack/Defense strategies to Generative Adversarial Networks

ACM Computing Surveys - 2021
Download the publication : ACM_CSUR_Survey_AdL.pdf [1.8Mo]  

BibTex references


@Article{DDM21,
author = {Yashar Deldjoo and Tommaso {Di Noia} and Felice Antonio Merra},
title = "A survey on Adversarial Recommender Systems: from
Attack/Defense strategies to Generative
Adversarial Networks",
journal = "ACM Computing Surveys",
year = "2021",
note = "Accepted for publication at ACM Computing Survey",
key = "Recommender System, Adversarial Machine Learning, Literature Review",
keywords = "Recommender System, Adversarial Machine Learning,
Literature Review",
url = "http://www-ictserv.poliba.it/publications/2021/DDM
21"
}

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SisInf Lab - Information Systems Laboratory

Research group of Politecnico di Bari
Edoardo Orabona St, 4 Bari, Italy