Speaker: Su Jia

Abstract: Dynamic pricing with unknown demand has been extensively studied and often formulated as a bandit problem. While well-understood theoretically, bandit-based policies are rarely deployed in the real world, since many of them overlooked practical constraints. For example, the price may oscillate, which is unfavorable in practice. We consider markdown policies, i.e. policies with non-increasing prices, and show tight regret bounds under various assumptions. Further, our results separates markdown pricing and unonstrained pricing, highlighting the extra complexity incurred by this monotonicity constraint.