Towards Effective Device-Aware Federated Learning. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001 (AI*IA, 2019)

How to Put Users in Control of their Data via Federated Pair-Wise Recommendation. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci (CoRR, 2020)

Prioritized multi-criteria federated learning. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001 (Intelligenza Artificiale, 2020)

FedeRank: User Controlled Feedback with Federated Recommender Systems. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci (ECIR (1), 2021)

How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Eugenio Di Sciascio; Tommaso Di Noia (IIR, 2021)

Sparse Embeddings for Recommender Systems with Knowledge Graphs. - Vito Walter Anelli; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Alberto Carlo Maria Mancino (IIR, 2021)

Pursuing Privacy in Recommender Systems: the View of Users and Researchers from Regulations to Applications. - Vito Walter Anelli; Luca Belli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci; Claudio Pomo (RecSys, 2021)

V-Elliot: Design, Evaluate and Tune Visual Recommender Systems. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Tommaso Di Noia (RecSys, 2021)

Sparse Feature Factorization for Recommender Systems with Knowledge Graphs. - Vito Walter Anelli; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Alberto Carlo Maria Mancino (RecSys, 2021)

How to put users in control of their data in federated top-N recommendation with learning to rank. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci (SAC, 2021)

Federated Recommender Systems with Learning to Rank. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci (SEBD, 2021)

Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco Maria Donini; Tommaso Di Noia (SIGIR, 2021)

Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Daniele Malitesta; Claudio Pomo (DL4SR@CIKM, 2022)

Addressing Privacy in Recommender Systems with Federated Learning. - Vito Walter Anelli; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Alberto Carlo Maria Mancino (IIR, 2022)

Fourth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). - Vito Walter Anelli; Pierpaolo Basile; Gerard de Melo; Francesco Maria Donini; Antonio Ferrara 001; Cataldo Musto; Fedelucio Narducci; Azzurra Ragone; Markus Zanker (RecSys, 2022)

How Neighborhood Exploration influences Novelty and Diversity in Graph Collaborative Filtering. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Daniele Malitesta; Claudio Pomo (MORS@RecSys, 2022)

The Challenging Reproducibility Task in Recommender Systems Research between Traditional and Deep Learning Models. - Vito Walter Anelli; Alejandro Bellogín; Antonio Ferrara 001; Daniele Malitesta; Felice Antonio Merra; Claudio Pomo; Francesco M. Donini; Eugenio Di Sciascio; Tommaso Di Noia (SEBD, 2022)

Inferring User Decision-Making Processes in Recommender Systems with Knowledge Graphs. - Vito Walter Anelli; Tommaso Di Noia; Eugenio Di Sciascio; Antonio Ferrara 001; Alberto Carlo Maria Mancino (SEBD, 2022)

User-controlled federated matrix factorization for recommender systems. - Vito Walter Anelli; Yashar Deldjoo; Tommaso Di Noia; Antonio Ferrara 001; Fedelucio Narducci (J. Intell. Inf. Syst., 2022)

Knowledge Graph Datasets for Recommendation. - Vincenzo Paparella; Alberto Carlo Maria Mancino; Antonio Ferrara 001; Claudio Pomo; Vito Walter Anelli; Tommaso Di Noia (KaRS@RecSys, 2023)

Fifth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). - Vito Walter Anelli; Pierpaolo Basile; Gerard de Melo; Francesco M. Donini; Antonio Ferrara 001; Cataldo Musto; Fedelucio Narducci; Azzurra Ragone; Markus Zanker (RecSys, 2023)

KGTORe: Tailored Recommendations through Knowledge-aware GNN Models. - Alberto Carlo Maria Mancino; Antonio Ferrara 001; Salvatore Bufi; Daniele Malitesta; Tommaso Di Noia; Eugenio Di Sciascio (RecSys, 2023)

An Out-of-the-Box Application for Reproducible Graph Collaborative Filtering extending the Elliot Framework. - Daniele Malitesta; Claudio Pomo; Vito Walter Anelli; Tommaso Di Noia; Antonio Ferrara 001 (UMAP (Adjunct Publication), 2023)

Report on the 13th Italian Information Retrieval Workshop (IIR 2023). - Guglielmo Faggioli; Antonio Ferrara 001; Franco Maria Nardini; Nicola Tonellotto (SIGIR Forum, 2023)

KGFlex: Efficient Recommendation with Sparse Feature Factorization and Knowledge Graphs. - Antonio Ferrara 001; Vito Walter Anelli; Alberto Carlo Maria Mancino; Tommaso Di Noia; Eugenio Di Sciascio (Trans. Recomm. Syst., 2023)

KGUF: Simple Knowledge-Aware Graph-Based Recommender with User-Based Semantic Features Filtering. - Salvatore Bufi; Alberto Carlo Maria Mancino; Antonio Ferrara 001; Daniele Malitesta; Tommaso Di Noia; Eugenio Di Sciascio (IRonGraphs, 2024)

Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). - Vito Walter Anelli; Antonio Ferrara 001; Cataldo Musto; Fedelucio Narducci; Azzurra Ragone; Markus Zanker (RecSys, 2024)

DIVAN: Deep-Interest Virality-Aware Network to Exploit Temporal Dynamics in News Recommendation. - Antonio Ferrara 001; Marco Valentini; Paolo Masciullo; Antonio De Candia; Davide Abbattista; Riccardo Fusco; Claudio Pomo; Vito Walter Anelli; Giovanni Maria Biancofiore; Ludovico Boratto; Fedelucio Narducci (RecSys Challenge, 2024)

DataRec: A Framework for Standardizing Recommendation Data Processing and Analysis. - Alberto Carlo Maria Mancino; Salvatore Bufi; Angela Di Fazio; Daniele Malitesta; Claudio Pomo; Antonio Ferrara 001; Tommaso Di Noia (CoRR, 2024)

Explainable brain age prediction: a comparative evaluation of morphometric and deep learning pipelines. - Maria Luigia Natalia De Bonis; Giuseppe Fasano; Angela Lombardi; Carmelo Ardito; Antonio Ferrara 001; Eugenio Di Sciascio; Tommaso Di Noia (Brain Informatics, 2024)

Enhancing Utility in Differentially Private Recommendation Data Release via Exponential Mechanism. - Antonio Ferrara 001; Angela Di Fazio; Alberto Carlo Maria Mancino; Tommaso Di Noia; Eugenio Di Sciascio (ECIR (3), 2025)

Enhancing Reproducibility and Replicability in Information Retrieval: A Path Towards Scientific Integrity and Effective Research. - Antonio Ferrara 001; Claudio Pomo; Nicola Tonellotto (ECIR (5), 2025)

DataRec: A Python Library for Standardized and Reproducible Data Management in Recommender Systems. - Alberto Carlo Maria Mancino; Salvatore Bufi; Angela Di Fazio; Antonio Ferrara 001; Daniele Malitesta; Claudio Pomo; Tommaso Di Noia (SIGIR, 2025)

Exploring Explainability in Federated Learning: A Comparative Study on Brain Age Prediction. - Giuseppe Fasano; Angela Lombardi; Antonio Ferrara 001; Eugenio Di Sciascio; Tommaso Di Noia (xAI (1), 2025)

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence. - Paolo Sorino; Angela Lombardi; Domenico Lofù; Tommaso Colafiglio; Antonio Ferrara 001; Fedelucio Narducci; Eugenio Di Sciascio; Tommaso Di Noia (Brain Informatics, 2025)