An intelligent electric vehicle charging system that uses reinforcement learning and stochastic dynamic programming to minimize charging costs while maintaining optimal battery health under uncertain ...

The goal is to implement, analyze, and compare various stochastic control techniques—from classical methods to modern machine learning approaches—with applications to real-world problems in portfolio ...

In this paper we study the problems of pricing and optimizing sidecar and collateralized reinsurance portfolios. The academic literature on sidecar portfolio optimization that takes into account the ...

Course in stochastic optimization with an emphasis on formulating, solving, and approximating optimization models under uncertainty. Topics include: Models and applications: extensions of the linear ...

Abstract: Bilevel optimization, where one optimization problem is inherently nested within another, has gained significant attention due to its extensive applications in machine learning, such as ...