Search Results for author: Fahd Husain

Found 2 papers, 2 papers with code

E Pluribus Unum: Guidelines on Multi-Objective Evaluation of Recommender Systems

1 code implementation • 20 Apr 2023 • Patrick John Chia, Giuseppe Attanasio, Jacopo Tagliabue, Federico Bianchi, Ciro Greco, Gabriel de Souza P. Moreira, Davide Eynard, Fahd Husain

Recommender Systems today are still mostly evaluated in terms of accuracy, with other aspects beyond the immediate relevance of recommendations, such as diversity, long-term user retention and fairness, often taking a back seat.

Fairness Model Selection +1

Paper
Code

EvalRS 2023. Well-Rounded Recommender Systems For Real-World Deployments

1 code implementation • 14 Apr 2023 • Federico Bianchi, Patrick John Chia, Ciro Greco, Claudio Pomo, Gabriel Moreira, Davide Eynard, Fahd Husain, Jacopo Tagliabue

EvalRS aims to bring together practitioners from industry and academia to foster a debate on rounded evaluation of recommender systems, with a focus on real-world impact across a multitude of deployment scenarios.

Fairness Informativeness +1

Paper
Code

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