Shai Chester

Speaker: Max Reppen (Boston University) Title: Neural Optimal Stopping Boundary Abstract:  A method based on deep artificial neural networks and empirical risk minimization is developed to calculate the boundary separating the stopping and continuation regions in optimal stopping. The algorithm parameterizes the stopping boundary as the graph of a function and introduces relaxed stopping rules based on fuzzy […]

Speaker: James Halverson (Northeastern University)   Title: Unexpected Uses of Neural Networks: Field Theory and Metric Flows Abstract:  We are now quite used to the idea that deep neural networks may be trained in a variety of ways to tackle cutting-edge problems in physics and mathematics, sometimes leading to rigorous results. In this talk, however, I will argue […]