102 citations · 165 across the 6 of their papers we have counts for
6 papers · 1 filter
Beyond Centralization: User-Controlled Federated Recommendations in Practice
Manel Slokom, Alejandro Bellogin
Recommendation systems typically require centralized user data, limiting user control and raising privacy concerns. Federated learning offers an alternative by keeping data on-devi…
Top-N Recommendation Algorithms: A Quest for the State-of-the-Art
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia +2
Research on recommender systems algorithms, like other areas of applied machine learning, is largely dominated by efforts to improve the state-of-the-art, typically in terms of acc…
Simulations for novel problems in recommendation: analyzing misinformation and data characteristics
Alejandro Bellogín, Yashar Deldjoo
In this position paper, we discuss recent applications of simulation approaches for recommender systems tasks. In particular, we describe how they were used to analyze the problem…
Adherence and Constancy in LIME-RS Explanations for Recommendation
Vito Walter Anelli, Alejandro Bellogín, Tommaso Di Noia +3
Explainable Recommendation has attracted a lot of attention due to a renewed interest in explainable artificial intelligence. In particular, post-hoc approaches have proved to be t…
Elliot: a Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
Vito Walter Anelli, Alejandro Bellogín, Antonio Ferrara +5
Recommender Systems have shown to be an effective way to alleviate the over-choice problem and provide accurate and tailored recommendations. However, the impressive number of prop…
Improving Accountability in Recommender Systems Research Through Reproducibility
Alejandro Bellogín, Alan Said
Reproducibility is a key requirement for scientific progress. It allows the reproduction of the works of others, and, as a consequence, to fully trust the reported claims and resul…