Malitesta, Daniele
Malitesta, Daniele
Dipartimento di Ingegneria Elettrica e dell'Informazione
0000-0003-2228-0333
A Study of Defensive Methods to Protect Visual Recommendation against Adversarial Manipulation of Images
2021-01-01 Anelli, Vito Walter; Deldjoo, Yashar; Di Noia, Tommaso; Malitesta, Daniele; Merra, Felice Antonio
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems
2021-01-01 Deldjoo, Y; Di Noia, T; Malitesta, D; Merra, Fa
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework
2023-01-01 Malitesta, D.; Pomo, C.; Anelli, V. W.; Di Noia, T.; Ferrara, A.
Assessing perceptual and recommendation mutation of adversarially-poisoned visual recommenders
2020-01-01 Anelli, Vito Walter; Di Noia, Tommaso; Malitesta, Daniele; Merra, Felice Antonio
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering
2023-01-01 Anelli, V. W.; Deldjoo, Y.; Di Noia, T.; Malitesta, D.; Paparella, V.; Pomo, C.
Deep Learning-Based Adaptive Image Compression System for a Real-World Scenario
2020-01-01 Anelli, Vito Walter; Deldjoo, Yashar; Di Noia, Tommaso; Malitesta, Daniele
Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries
2023-01-01 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
2021-01-01 Anelli, Vito Walter; Bellogin, Alejandro; Ferrara, Antonio; Malitesta, Daniele; Merra, Felice Antonio; Pomo, Claudio; Maria Donini, Francesco; Di Noia, Tommaso
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective
2023-01-01 Di Palma, D.; Anelli, V. W.; Malitesta, D.; Paparella, V.; Pomo, C.; Deldjoo, Y.; Di Noia, T.
Formalizing Multimedia Recommendation through Multimodal Deep Learning
2024-01-01 Malitesta, Daniele; Cornacchia, Giandomenico; Pomo, Claudio; Merra, Felice Antonio; Di Noia, Tommaso; Di Sciascio, Eugenio
Graph neural networks for recommendation leveraging multimodal information
2024-01-01 Malitesta, Daniele
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering
2022-01-01 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
2021-01-01 Anelli, V. W.; Bellogin, A.; 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
2023-01-01 Mancino, A. C. M.; Ferrara, A.; Bufi, S.; Malitesta, D.; Di Noia, T.; Di Sciascio, E.
Leveraging Content-Style Item Representation for Visual Recommendation
2022-01-01 Deldjoo, Yashar; Di Noia, Tommaso; Malitesta, Daniele; Merra, Felice Antonio
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews
2022-01-01 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
2020-01-01 Di Noia, Tommaso; Malitesta, Daniele; Merra, Felice Antonio
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models
2022-01-01 Anelli, V. W.; Bellogin, A.; 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
2021-01-01 Anelli, V. W.; Bellogin, A.; Ferrara, A.; Malitesta, D.; Merra, F. A.; Pomo, C.; Donini, F. M.; Di Noia, T.