Merra, Felice Antonio

Merra, Felice Antonio  

Dipartimento di Ingegneria Elettrica e dell'Informazione  

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Risultati 1 - 20 di 23 (tempo di esecuzione: 0.052 secondi).
Titolo Data di pubblicazione Autori File
A Formal Analysis of Recommendation Quality of Adversarially-trained Recommenders 1-gen-2021 Anelli V. W.Deldjoo Y.Di Noia T.Merra F. A.
A regression framework to interpret the robustness of recommender systems against shilling attacks 1-gen-2021 Deldjoo Y.Di Noia T.Di Sciascio E.Merra F. A.
A Study of Defensive Methods to Protect Visual Recommendation against Adversarial Manipulation of Images 1-gen-2021 Vito Walter AnelliYashar DeldjooTommaso Di NoiaDaniele MalitestaFelice Antonio Merra
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems 1-gen-2021 Deldjoo, YDi Noia, TMalitesta, DMerra, FA
A Survey on Adversarial Recommender Systems: From Attack/Defense Strategies to Generative Adversarial Networks 1-gen-2021 Yashar DeldjooTommaso Di NoiaFelice Antonio Merra
Adversarial Learning for Recommendation: Applications for Security and Generative Tasks — Concept to Code 1-gen-2020 Vito Walter AnelliYashar DeldjooTommaso Di NoiaFelice Antonio Merra
Adversarial Machine Learning in Recommender Systems 1-gen-2022 Merra, Felice Antonio
Adversarial machine learning in recommender systems (AML-RECSYS) 1-gen-2020 Yashar DeldjooTommaso Di NoiaFelice Antonio Merra
Adversarial Recommender Systems: Attack, Defense, and Advances 1-gen-2022 Anelli, Vito WalterDeldjoo, YasharDi Noia, TommasoMerra, Felice Antonio
Assessing perceptual and recommendation mutation of adversarially-poisoned visual recommenders 1-gen-2020 Vito Walter AnelliTommaso Di NoiaDaniele MalitestaFelice Antonio Merra
Assessing the impact of a user-item collaborative attack on class of users 1-gen-2019 Yashar DeldjooTommaso Di NoiaFelice Antonio Merra
Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries 1-gen-2023 Merra F. A.Anelli V. W.Di Noia T.Malitesta D.Mancino A. C. M.
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation 1-gen-2021 Vito Walter AnelliAntonio FerraraDaniele MalitestaFelice Antonio MerraClaudio PomoTommaso Di Noia +
Formalizing Multimedia Recommendation through Multimodal Deep Learning 1-gen-2024 Malitesta, DanieleCornacchia, GiandomenicoPomo, ClaudioMerra, Felice AntonioDi Noia, TommasoDi Sciascio, Eugenio
How Dataset Characteristics Affect the Robustness of Collaborative Recommendation Models 1-gen-2020 Yashar DeldjooTommaso Di NoiaEugenio Di SciascioFelice Antonio Merra
How to perform reproducible experiments in the ELLIOT recommendation framework: Data processing, model selection, and performance evaluation 1-gen-2021 Anelli V. W.Ferrara A.Malitesta D.Merra F. A.Pomo C.Donini F. M.Di Sciascio E.Di Noia T. +
Knowledge-enhanced Shilling Attacks for Recommendation 1-gen-2020 Vito Walter AnelliYashar DeldjooTommaso Di NoiaFelice Antonio MerraGiuseppe AccianiEugenio Di Sciascio
Leveraging Content-Style Item Representation for Visual Recommendation 1-gen-2022 Yashar DeldjooTommaso Di NoiaDaniele MalitestaFelice Antonio Merra
MSAP: Multi-Step Adversarial Perturbations on Recommender Systems Embeddings 1-gen-2021 Vito Walter AnelliYashar DeldjooTommaso Di NoiaFelice Antonio Merra +
SAShA: Semantic-Aware Shilling Attacks on Recommender Systems Exploiting Knowledge Graphs 1-gen-2020 Vito Walter AnelliYashar DeldjooTommaso Di NoiaEugenio Di SciascioFelice Antonio Merra