3 papers
cs.LG2026
Deep Hilbert--Galerkin Methods for Infinite-Dimensional PDEs and Optimal Control
Samuel N. Cohen, Filippo de Feo, Jackson Hebner +1
We develop deep learning-based approximation methods for fully nonlinear second-order PDEs on separable Hilbert spaces, such as HJB equations for infinite-dimensional control, by p…
math.OC2026
Duality methods in stochastic optimal control
Peter Bank, Filippo de Feo
We prove two duality descriptions of the value function for a generic stochastic optimal control problem. These yield sharp bounds for the value function and also hold when the dif…
math.OC2026
Optimal control of stochastic Volterra integral equations with completely monotone kernels and stochastic differential equations on Hilbert spaces with unbounded control and diffusion operators
Gabriele Bolli, Filippo de Feo
The dynamic programming approach is one of the most powerful ones in optimal control. However, when dealing with optimal control problems of stochastic Volterra integral equations…