A Note on Tight Lower Bound for MNL-Bandit Assortment Selection Models.

arXiv: Machine Learning（2018）

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摘要

In this note we prove a tight lower bound for the MNL-bandit assortment selection model that matches the upper bound given in (Agrawal et al., 2016a,b) for all parameters, up to logarithmic factors.

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