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Phase Transitions in Learning and Earning under Price Protection Guarantee
We consider a setting where a firm sells a product over a horizon of $T$ time steps.
Self-adapting Robustness in Demand Learning
We also show that ARL, by being conscious of both model ambiguity and revenue, bridges the gap between a distributionally robust policy and a follow-the-leader policy, which focus on model ambiguity and revenue, respectively.
Algorithmic Transparency with Strategic Users
We show that, in some cases, even the predictive power of machine learning algorithms may increase if the firm makes them transparent.
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