题　目：Data-Driven Operations: Safety, Fairness, and Beyond

嘉　宾：朱睿豪，助理教授，康奈尔大学

主持人：孙海龙 助理教授 上海交通大学安泰经济与管理学院

时　间：2023年9月13日（周三）14:00-15:30pm

地　点：安泰经济与管理学院A403

内容简介：

In this talk, we will discuss data-driven decision-making under constraints. It consists of two parts: 1. Motivated by practical needs of experimentation and policy learning in online systems, we study the problem of safe data collection. Specifically, we develop a logging policy that efficiently explores different actions to elicit information while achieving competitive reward compared with a baseline production policy. We first show that a common practice of mixing the production policy with randomized exploration, despite being safe, is sub-optimal in maximizing information gain. Then, we propose a safe optimal logging policy via a novel water-filling technique. Along the way, we discuss the generalization of our method to more practical scenarios and its implications to both offline and online policy learning. 2. We study the impact of price protection guarantee on dynamic pricing with initially unknown customer demand. Under the price protection guarantee, a customer who purchased a product in the past can receive a refund from the seller during the so-called price protection period in case the seller decides to lower the price. We characterize the regret lower and upper bound for this problem. Our results reveal the surprising phase transitions of the optimal regret with respect to the length of price protection period M. Specifically, when M is not too large, the optimal regret has no major difference when compared to that of the classic setting with no price protection guarantee. We also show that there exists an upper limit on how much the optimal regret can deteriorate when M grows large. The papers are available at: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3959086 and https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4265182.

演讲人简介：

Ruihao Zhu is currently an Assistant Professor at Cornell University SC Johnson College of Business. He mainly works on data-driven operations with applications in revenue management and supply chain. Previously, he received his PhD degree from MIT and his bachelor degrees from Shanghai Jiao Tong University and University of Michigan.

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