In this talk, we discuss recent advances in modeling, statistics, and computational methods for optimal transport-based distributionally robust optimization (DRO) - which encompasses divergence-based DRO as a particular case. We discuss, for example, motivating formulations which include distributionally pricing and hedging with martingale constraints, portfolio optimization, and Bayesian non-parametric inverse problems. As we present these settings, we discuss optimal sample complexity approximations and iterative optimization algorithms for these types of problems.

Place: Zoom:     https://arizona.zoom.us/j/81337180102 Password:   applied