Dynamic stochastic matching problems arise in a variety of recent applications, ranging from ridesharing and online video games to kidney exchange. Such problems are naturally formulated as Markov ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

Change-point detection is a pivotal statistical framework used to identify abrupt changes in the behaviour of stochastic systems. These models, which integrate inherent randomness, are essential in ...