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Our upcoming event for the Statistics Department Colloquium Series is scheduled for this Monday, November 21st from 12:00 – 1:00pm (ET) and will be an in-person presentation Science Center Rm. 316. The speaker will be Yongyi Guo who is a postdoctoral research fellow in the Department of Statistics, Harvard University, hosted by Professor Susan A. Murphy. In the fall of 2023, she will start as an assistant professor at the Department of Statistics, University of Wisconsin-Madison.
Title: A statistical approach to feature-based dynamic pricing
Abstract: Dynamic pricing is one of the most common examples of online decision problems. With the development of e-commerce and the massive real-time data in online platforms today, feature-based pricing has become increasingly important. Semi-parametric feedback structure (caused by unknown market noise distribution) is a natural formulation in such problems, and benefits from tools from non-parametric statistical estimation. In this work, we study feature-based dynamic pricing with semi-parametric feedback structure (unknown market noise distribution). We propose a dynamic learning and decision algorithm that makes use of the classical idea of tradeoff between exploration (statistical estimation) and exploitation (reward optimization). Under mild conditions, our proposed algorithm achieves near optimal regret in terms of dependence on the time horizon. This result offers a new perspective on combining statistical learning and decision making in the online decision context.