| Yijie Peng
北京大学工业工程与管理系助理教授
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【主讲】彭一杰，助理教授，北京大学工业工程与管理系
Dr. Yijie Peng is currently an assistant professor of the Department of Industrial Engineering and Management at Peking University (PKU). He received his Ph.D. from the Department of Management Science at Fudan University and his B.S. degree from the School of Mathematics at Wuhan University. Before joining PKU, he worked as an assistant professor at George Mason University, and postdoctoral scholar at Fudan University and R.H. Smith School of Business at University of Maryland at College Park. Many of his publications appear in high-quality journals including Operations Research, IEEE Transactions on Automatic Control, INFORMS Journal on Computing, Journal of Discrete Event Dynamic System, and Quantitative Finance. His research interests include stochastic modeling and analysis, simulation optimization, machine learning, data analytics, and healthcare.
【Speaker】Yijie Peng, Assistant Professor，the Department of Industrial Engineering and Management, Peking University.
【Topic】Generalized Likelihood Ratio Method and Its Applications
【Time】Thursday, Mar 7, 2019, 10:00 am
【Venue】Room 453, Weilun Building, Tsinghua SEM
【Organizer】Department of Management Science and Engineering
【Abstract】We propose a generalized likelihood ratio (GLR) estimator in a framework that can handle discontinuous sample performances with structural parameters. This work extends the three most popular unbiased stochastic derivative estimators: (1) infinitesimal perturbation analysis (IPA), (2) the likelihood ratio (LR) method, (3) the weak derivative method, to a setting where they did not previously apply. The GLR estimator can deal with many applications in a single umbrella and preserves the single-run efficiency of the classic IPA-LR estimators. Particularly, we present three applications of the GLR estimator in financial engineering, healthcare, and artificial intelligence.
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