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cs.IR2024★ 5 cited
Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies
Chih-Wei Hsu, Martin Mladenov, Ofer Meshi +8
Evaluation of policies in recommender systems typically involves A/B testing using live experiments on real users to assess a new policy's impact on relevant metrics. This ``gold s…
cs.IR2023
Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics
Guy Tennenholtz, Martin Mladenov, Nadav Merlis +2
While popularity bias is recognized to play a crucial role in recommmender (and other ranking-based) systems, detailed analysis of its impact on collective user welfare has largely…