Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank. - Edoardo D'Amico; Giovanni Gabbolini; Daniele Montesi; Matteo Moreschini; Federico Parroni; Federico Piccinini; Alberto Rossettini; Alessio Russo Introito; Cesare Bernardis; Maurizio Ferrari Dacrema (RecSys Challenge, 2019)

On the instability of embeddings for recommender systems: the case of matrix factorization. - Giovanni Gabbolini; Edoardo D'Amico; Cesare Bernardis; Paolo Cremonesi (SAC, 2021)

Analyzing and improving stability of matrix factorization for recommender systems. - Edoardo D'Amico; Giovanni Gabbolini; Cesare Bernardis; Paolo Cremonesi (J. Intell. Inf. Syst., 2022)

Item Graph Convolution Collaborative Filtering for Inductive Recommendations. - Edoardo D'Amico; Khalil Muhammad; Elias Z. Tragos; Barry Smyth; Neil Hurley; Aonghus Lawlor (ECIR (1), 2023)

Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. - Aayush Singha Roy; Edoardo D'Amico; Aonghus Lawlor; Neil Hurley (FLAIRS, 2023)

Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation. - Edoardo D'Amico; Aonghus Lawlor; Neil Hurley (PAKDD (3), 2023)

Scalable Deep Q-Learning for Session-Based Slate Recommendation. - Aayush Singha Roy; Edoardo D'Amico; Elias Z. Tragos; Aonghus Lawlor; Neil Hurley (RecSys, 2023)

Rs4rs: Semantically Find Recent Publications from Top Recommendation System-Related Venues. - Tri Kurniawan Wijaya; Edoardo D'Amico; Gábor Fodor 002; Manuel V. Loureiro (RecSys, 2024)

RBoard: A Unified Platform for Reproducible and Reusable Recommender System Benchmarks. - Xinyang Shao; Edoardo D'Amico; Gábor Fodor 002; Tri Kurniawan Wijaya (CoRR, 2024)

Dataset-Agnostic Recommender Systems. - Tri Kurniawan Wijaya; Edoardo D'Amico; Xinyang Shao (CoRR, 2025)

Universal Reusability in Recommender Systems: The Case for Dataset- and Task-Independent Frameworks. - Tri Kurniawan Wijaya; Xinyang Shao; Gonzalo Fiz Pontiveros; Edoardo D'Amico (CoRR, 2025)

Evaluating Podcast Recommendations with Profile-Aware LLM-as-a-Judge. - Francesco Fabbri; Gustavo Penha; Edoardo D'Amico; Alice Wang; Marco De Nadai; Jackie Doremus; Paul Gigioli; Andreas Damianou; Oskar Stal; Mounia Lalmas (CoRR, 2025)

Semantic IDs for Joint Generative Search and Recommendation. - Gustavo Penha; Edoardo D'Amico; Marco De Nadai; Enrico Palumbo; Alexandre Tamborrino; Ali Vardasbi; Max Lefarov; Shawn Lin; Timothy Christopher Heath; Francesco Fabbri; Hugues Bouchard (CoRR, 2025)