Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning
Jan 1, 2024·

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Dake Zhang
Boxiang Lyu
Shuang Qiu
Mladen Kolar
Tong Zhang

Authors
PhD (2019-2024)
Boxiang Lyu was a PhD student in the Econometrics and Statistics dissertation area at University of Chicago Booth School of Business. Prior to Booth, he obtained a Master of Science in Machine Learning (2019) and a Bachelor of Science in Statistics and Machine Learning (2018) from Carnegie Mellon University.


Authors
Professor of Data Sciences and Operations
Mladen Kolar is a Professor of Data Sciences and Operations at the University of Southern California Marshall School of Business and a Visiting Professor of Statistics and Data Science at Mohamed bin Zayed University of Artificial Intelligence. Before joining USC, he was on the faculty of the University of Chicago Booth School of Business. His research is focused on high-dimensional statistical methods, graphical models, varying-coefficient models and data mining, driven by the need to uncover interesting and scientifically meaningful structures from observational data. He is a Fellow of the Institute of Mathematical Statistics.