题目: Bayesian Risk Optimization (BRO): A New Approach to Data-driven Stochastic Optimization

贝叶斯风险优化：数据驱动随机优化的一种新方法

演讲人: 周恩露，佐治亚理工学院

时间:2020年11月26日上午10:00

参与方式:zoom云视频会议；

会议号: 67995839061 会议密码: 258415

讲座摘要:

Large class of stochastic programs involve optimizing an expectation taken with respect to an underlying distribution that is unknown in practice. One popular approach to addressing the distributional uncertainty, known as the distributionally robust optimization (DRO), is to hedge against the worst case over an uncertainty set of candidate distributions. However, it has been observed that inappropriate construction of the uncertainty set can sometimes result in over-conservative solutions. To explore the middle ground between optimistically ignoring the distributional uncertainty and pessimistically fixating on the worst-case scenario, we propose a Bayesian risk optimization (BRO) framework for parametric underlying distributions, which is to optimize a risk functional applied to the posterior distribution of an unknown distribution parameter. Of our particular interest are four risk functionals: mean, mean-variance, value-at-risk, and conditional value-at-risk. To reveal the implication of BRO, we establish the consistency of objective functions and optimal solutions, as well as the asymptotic normality of objective functions and optimal values. We also develop algorithms to solve BRO formulations, and consider the extension of BRO to the online setting.

演讲嘉宾简介:

Enlu Zhou is currently an associate professor in the School of Industrial & Systems Engineering at Georgia Institute of Technology. She received the B.S. degree with highest honors in electrical engineering from Zhejiang University, China, in 2004, and the Ph.D. degree in electrical engineering from the University of Maryland, College Park, in 2009. From 2009-2013 she was an assistant professor in the Industrial & Enterprise Systems Engineering Department at the University of Illinois Urbana-Champaign, and since 2013 she has been in the School of Industrial & Systems Engineering at Georgia Tech. She is a recipient of the Best Theoretical Paper award at the Winter Simulation Conference, AFOSR Young Investigator award, and NSF CAREER award. She has served or is currently serving as an associate editor for Journal of Simulation, IEEE Transactions on Automatic Control, and Operations Research.