Malitesta, Daniele

Malitesta, Daniele  

Dipartimento di Ingegneria Elettrica e dell'Informazione  

Dottorandi  

0000-0003-2228-0333

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Risultati 1 - 18 di 18 (tempo di esecuzione: 0.03 secondi).
Titolo Data di pubblicazione Autori File
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
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework 1-gen-2023 Malitesta D.Pomo C.Anelli V. W.Di Noia T.Ferrara A.
Assessing perceptual and recommendation mutation of adversarially-poisoned visual recommenders 1-gen-2020 Vito Walter AnelliTommaso Di NoiaDaniele MalitestaFelice Antonio Merra
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering 1-gen-2023 Anelli V. W.Deldjoo Y.Di Noia T.Malitesta D.Pomo C. +
Deep Learning-Based Adaptive Image Compression System for a Real-World Scenario 1-gen-2020 Vito Walter AnelliYashar DeldjooTommaso Di NoiaDaniele Malitesta
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 +
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective 1-gen-2023 Di Palma D.Anelli V. W.Malitesta D.Pomo C.Deldjoo Y.Di Noia T. +
Graph neural networks for recommendation leveraging multimodal information 1-gen-2024 Malitesta, Daniele
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering 1-gen-2022 Anelli V. W.Deldjoo Y.Di Noia T.Di Sciascio E.Ferrara A.Malitesta D.Pomo C.
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. +
KGTORe: Tailored Recommendations through Knowledge-aware GNN Models 1-gen-2023 Mancino A. C. M.Ferrara A.Bufi S.Malitesta D.Di Noia T.Di Sciascio E.
Leveraging Content-Style Item Representation for Visual Recommendation 1-gen-2022 Yashar DeldjooTommaso Di NoiaDaniele MalitestaFelice Antonio Merra
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews 1-gen-2022 Anelli V. W.Deldjoo Y.Di Noia T.Di Sciascio E.Ferrara A.Malitesta D.Pomo C.
TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems 1-gen-2020 Tommaso Di NoiaDaniele MalitestaFelice Antonio Merra
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models 1-gen-2022 Anelli V. W.Ferrara A.Malitesta D.Merra F. A.Pomo C.Donini F. M.Di Sciascio E.Di Noia T. +
V-Elliot: Design, evaluate and tune visual recommender systems 1-gen-2021 Anelli V. W.Ferrara A.Malitesta D.Merra F. A.Pomo C.Donini F. M.Di Noia T. +