2 papers
cs.IR2024
Social Choice for Heterogeneous Fairness in Recommendation
Amanda Aird, Elena Štefancová, Cassidy All +4
Algorithmic fairness in recommender systems requires close attention to the needs of a diverse set of stakeholders that may have competing interests. Previous work in this area has…
cs.IR2024
Data Generation via Latent Factor Simulation for Fairness-aware Re-ranking
Elena Stefancova, Cassidy All, Joshua Paup +3
Synthetic data is a useful resource for algorithmic research. It allows for the evaluation of systems under a range of conditions that might be difficult to achieve in real world s…