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Daniele Malitesta
ORCID
Publication Activity (10 Years)
Years Active: 2020-2023
Publications (10 Years): 30
Top Topics
Convolutional Neural Networks
Collaborative Filtering
Human Perceptual
Deep Learning
Top Venues
CoRR
RecSys
SIGIR
IIR
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Publications
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Daniele Malitesta
,
Claudio Pomo
,
Vito Walter Anelli
,
Alberto Carlo Maria Mancino
,
Eugenio Di Sciascio
,
Tommaso Di Noia
A Topology-aware Analysis of Graph Collaborative Filtering.
CoRR
(2023)
Daniele Malitesta
,
Giandomenico Cornacchia
,
Claudio Pomo
,
Tommaso Di Noia
On Popularity Bias of Multimodal-aware Recommender Systems: A Modalities-driven Analysis.
MMIR@MM
(2023)
Daniele Malitesta
,
Giuseppe Gassi
,
Claudio Pomo
,
Tommaso Di Noia
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation.
CoRR
(2023)
Vito Walter Anelli
,
Yashar Deldjoo
,
Tommaso Di Noia
,
Daniele Malitesta
,
Vincenzo Paparella
,
Claudio Pomo
Auditing Consumer- and Producer-Fairness in Graph Collaborative Filtering.
ECIR (1)
(2023)
Daniele Malitesta
,
Giandomenico Cornacchia
,
Claudio Pomo
,
Tommaso Di Noia
Disentangling the Performance Puzzle of Multimodal-aware Recommender Systems.
EvalRS@KDD
(2023)
Daniele Malitesta
,
Giuseppe Gassi
,
Claudio Pomo
,
Tommaso Di Noia
Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation.
ACM Multimedia
(2023)
Daniele Malitesta
,
Claudio Pomo
,
Vito Walter Anelli
,
Tommaso Di Noia
,
Antonio Ferrara
An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework.
UMAP (Adjunct Publication)
(2023)
Daniele Malitesta
,
Giandomenico Cornacchia
,
Claudio Pomo
,
Felice Antonio Merra
,
Tommaso Di Noia
,
Eugenio Di Sciascio
Formalizing Multimedia Recommendation through Multimodal Deep Learning.
CoRR
(2023)
Dario Di Palma
,
Vito Walter Anelli
,
Daniele Malitesta
,
Vincenzo Paparella
,
Claudio Pomo
,
Yashar Deldjoo
,
Tommaso Di Noia
Examining Fairness in Graph-Based Collaborative Filtering: A Consumer and Producer Perspective.
IIR
(2023)
Daniele Malitesta
,
Giandomenico Cornacchia
,
Claudio Pomo
,
Tommaso Di Noia
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis.
CoRR
(2023)
Vito Walter Anelli
,
Daniele Malitesta
,
Claudio Pomo
,
Alejandro Bellogín
,
Tommaso Di Noia
,
Eugenio Di Sciascio
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis.
CoRR
(2023)
Felice Antonio Merra
,
Vito Walter Anelli
,
Tommaso Di Noia
,
Daniele Malitesta
,
Alberto Carlo Maria Mancino
Denoise to Protect: A Method to Robustify Visual Recommenders from Adversaries.
SIGIR
(2023)
Alberto Carlo Maria Mancino
,
Antonio Ferrara
,
Salvatore Bufi
,
Daniele Malitesta
,
Tommaso Di Noia
,
Eugenio Di Sciascio
KGTORe: Tailored Recommendations through Knowledge-aware GNN Models.
RecSys
(2023)
Vito Walter Anelli
,
Daniele Malitesta
,
Claudio Pomo
,
Alejandro Bellogín
,
Eugenio Di Sciascio
,
Tommaso Di Noia
Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis.
RecSys
(2023)
Daniele Malitesta
,
Claudio Pomo
,
Tommaso Di Noia
Graph Neural Networks for Recommendation: Reproducibility, Graph Topology, and Node Representation.
CoRR
(2023)
Vito Walter Anelli
,
Yashar Deldjoo
,
Tommaso Di Noia
,
Eugenio Di Sciascio
,
Antonio Ferrara
,
Daniele Malitesta
,
Claudio Pomo
How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering.
MORS@RecSys
(2022)
Vito Walter Anelli
,
Alejandro Bellogín
,
Antonio Ferrara
,
Daniele Malitesta
,
Felice Antonio Merra
,
Claudio Pomo
,
Francesco M. Donini
,
Eugenio Di Sciascio
,
Tommaso Di Noia
The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models.
SEBD
(2022)
Yashar Deldjoo
,
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
Leveraging Content-Style Item Representation for Visual Recommendation.
ECIR (2)
(2022)
Vito Walter Anelli
,
Yashar Deldjoo
,
Tommaso Di Noia
,
Eugenio Di Sciascio
,
Antonio Ferrara
,
Daniele Malitesta
,
Claudio Pomo
Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews.
DL4SR@CIKM
(2022)
Vito Walter Anelli
,
Yashar Deldjoo
,
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images.
SIGIR
(2021)
Vito Walter Anelli
,
Alejandro Bellogín
,
Antonio Ferrara
,
Daniele Malitesta
,
Felice Antonio Merra
,
Claudio Pomo
,
Francesco Maria Donini
,
Eugenio Di Sciascio
,
Tommaso Di Noia
How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation.
IIR
(2021)
Vito Walter Anelli
,
Alejandro Bellogín
,
Antonio Ferrara
,
Daniele Malitesta
,
Felice Antonio Merra
,
Claudio Pomo
,
Francesco M. Donini
,
Tommaso Di Noia
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation.
CoRR
(2021)
Vito Walter Anelli
,
Tommaso Di Noia
,
Eugenio Di Sciascio
,
Daniele Malitesta
,
Felice Antonio Merra
Adversarial Attacks against Visual Recommendation: an Investigation on the Influence of Items' Popularity.
OHARS@RecSys
(2021)
Vito Walter Anelli
,
Alejandro Bellogín
,
Antonio Ferrara
,
Daniele Malitesta
,
Felice Antonio Merra
,
Claudio Pomo
,
Francesco Maria Donini
,
Tommaso Di Noia
V-Elliot: Design, Evaluate and Tune Visual Recommender Systems.
RecSys
(2021)
Vito Walter Anelli
,
Alejandro Bellogín
,
Antonio Ferrara
,
Daniele Malitesta
,
Felice Antonio Merra
,
Claudio Pomo
,
Francesco Maria Donini
,
Tommaso Di Noia
Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation.
SIGIR
(2021)
Yashar Deldjoo
,
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
A Study on the Relative Importance of Convolutional Neural Networks in Visually-Aware Recommender Systems.
CVPR Workshops
(2021)
Vito Walter Anelli
,
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
Assessing Perceptual and Recommendation Mutation of Adversarially-Poisoned Visual Recommenders (short paper).
DP@AI*IA
(2020)
Vito Walter Anelli
,
Yashar Deldjoo
,
Tommaso Di Noia
,
Daniele Malitesta
Deep Learning-Based Adaptive Image Compression System for a Real-World Scenario.
EAIS
(2020)
Vito Walter Anelli
,
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
An Empirical Study of DNNs Robustification Inefficacy in Protecting Visual Recommenders.
CoRR
(2020)
Tommaso Di Noia
,
Daniele Malitesta
,
Felice Antonio Merra
TAaMR: Targeted Adversarial Attack against Multimedia Recommender Systems.
DSN Workshops
(2020)