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 paper investigates conditions under which stochastic dynamic programs easily reduce to static deterministic programs. The conditions, though strict, are still rich enough to aid in the solution ...

Stochastic Sauna is a traditional workshop that brings together researchers and students working on probability, statistics, and their applications. The 2022 occasion will be held on 20th December ...

Professor Ruszczynski’s interests are in the theory, numerical methods and applications of stochastic optimization. He is author of "Nonlinear Optimization", "Lectures on Stochastic programming", and ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

We investigate risk-averse stochastic optimization problems with a risk-shaping constraint in the form of a stochastic-order relation. Both univariate and multivariate orders are considered. We extend ...