Workshop Report 21w5167 Optimization under Uncertainty: Learning and Decision Making in 2021

Abstract

This workshop brought together researchers in optimization under uncertainty and uncertainty quantification, whose work stands to benefit from cutting-edge machine learning techniques for data-driven differential equations. The workshop focused on mathematical challenges at the interface of applied mathematics, optimization, probability and statistics, and machine learning. Through eleven scientific talks, three panel discussions, and unstructured interactions, the workshop facilitated an exchange of ideas towards new, powerful methods for optimization under uncertainty. In what follows, we give an overview of the presentations, discussions, and outcomes.