most citedA Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits

3 citations · 3 across the 1 of their papers we have counts for

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cs.IR2023★ 3 cited

A Field Test of Bandit Algorithms for Recommendations: Understanding the Validity of Assumptions on Human Preferences in Multi-armed Bandits

Liu Leqi, Giulio Zhou, Fatma Kılınç-Karzan +2

Personalized recommender systems suffuse modern life, shaping what media we read and what products we consume. Algorithms powering such systems tend to consist of supervised learni…