【新时代物流沙龙第58期】Adaptive Sampling-based Nonconvex and Nonsmooth approaches for Stochastic Programs with Implicitly Decision-dependent Uncertainty
时间：2024年11月14日（周四） 10:30-12:00 地点：思源东楼611 报告人简介：刘俊驿，清华大学工业工程系准聘副教授。2019年于美国南加州大学获得工业与系统工程博士学位。2023年入选国家级青年人才项目。目前研究方向为随机优化，侧重随机优化与统计、机器学习的交叉研究。以第一作者身份在Operations Research, Mathematics of Operations Research, SIAM Journal on Optimization 等国际学术期刊上发表多篇文章。 报告摘要：We consider a class of stochastic programming problems where the implicitly decision-dependent random variable follows a nonparametric regression model with heteroskedastic error. To deal with the computational difficulty resulted from the latent decision dependency, we develop an adaptive sampling-based surrogate method that integrates the simulation scheme and statistical estimates in a way that the simulation process is adaptively guided by the algorithmic procedure.
