Abstract:

In this talk I will discuss the key connections and differences between the model-based and model-free paradigms from the perspectives of reinforcement learning and generative AI. I will argue that establishing a sufficiently accurate model is both impossible and unnecessary for the ultimate purpose of making optimal decisions, but there is some quantity, one that is an aggregate measure of the model parameters and control actions,  that needs to be learned and can indeed be learned efficiently in a data-driven way.

 

Bio

Xunyu Zhou is the Liu Family Professor of Industrial Engineering and Operations Research at Columbia University in New York. He was the Nomura Professor of Mathematical Finance, the Director of Nomura Center for Mathematical Finance and the Director of Oxford-Nie Financial Big Data Lab at University of Oxford during 2007-2016 before joining Columbia.

He is well known for his work in indefinite stochastic LQ control theory and application to dynamic mean—variance portfolio selection, in asset allocation and pricing under cumulative prospect theory, and in general time inconsistent problems. His current research focuses on reinforcement learning in continuous time with possibly continuous state and action spaces and applications to generative AI and intelligent wealth management solutions. He directs the Nie Center for Intelligent Asset Management, a research center funded by a FinTech company, at Columbia.  He has addressed the 2010 International Congress of Mathematicians, and has been awarded the Wolfson Research Award from The Royal Society (UK), the Outstanding Paper Prize from the Society for Industrial and Applied Mathematics, the Humboldt Distinguished Lecturer, the Alexander von Humboldt Research Fellowship, the Archimedes Lecturer at Columbia, and Distinguished Faculty Teaching Award at Columbia University.  He is both an IEEE Fellow and a SIAM Fellow.

Professor Zhou received his Ph.D. in Operations Research and Control Theory from Fudan University in China in 1989.

 

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https://us06web.zoom.us/j/89178730704?pwd=7rpkhbdSO9jEH3dTq4jmwnn0tEzmvN.1

Meeting ID: 891 7873 0704

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