A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images

The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, page 10 - 2021
Download the publication : SIGIR2021_A_Study_of_Defensive_Methods_to_Protect_Visual_Recommendation_Against_Adversarial_Manipulation_of_Images.pdf [1.2Mo]  

BibTex references


@InProceedings{ADDMM21,
author = {Vito Walter Anelli and Yashar Deldjoo and Tommaso {Di Noia} and Daniele Malitesta and Felice Antonio Merra},
title = "A Study of Defensive Methods to Protect Visual
Recommendation Against Adversarial Manipulation of
Images",
booktitle = "The 44th International ACM SIGIR Conference on
Research and Development in Information Retrieval",
pages = "10",
year = "2021",
publisher = "ACM",
note = "https://doi.org/10.1145/3404835.3462848",
keywords = "Adversarial Machine Learning; Recommender System;
Multimedia Recommendation",
url = "http://www-ictserv.poliba.it/publications/2021/ADD
MM21"
}

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SisInf Lab - Information Systems Laboratory

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