5 papers
Low-rank kernel methods for American option pricing
Michael Multerer, Paul Schneider, Chiara Segala
We propose a scalable and theoretically grounded low-rank conditional expectation model for recursive Monte Carlo optimal stopping problems, in particular American option pricing.…
Tree-Adaptive Multiscale Kernel Lasso in Samplet Coordinates
Sara Avesani, Gaia Fumagalli, Michael Multerer +1
We develop a novel framework for sparse multiscale kernel approximation of large scattered data problems based on a samplet representation. Samplets form a multiresolution analysis…
Sparse stabilization of mean-field agent dynamics through a three-operator splitting method
Giacomo Albi, Dante Kalise, Chiara Segala +1
We study the sparse stabilization of nonlinear multi-agent systems within a mean-field optimal control framework. The goal is to drive large populations of interacting agents towar…
Sparse control in microscopic and mean-field leader-follower models
Melanie Harms, Michael Herty, Chiara Segala +1
This work investigates the decay properties of Lyapunov functions in leader-follower systems seen as a sparse control framework. Starting with a microscopic representation, we esta…
The turnpike control in stochastic multi-agent dynamics: a discrete-time approach with exponential integrators
Fabio Cassini, Chiara Segala
In this manuscript, we study the turnpike property in stochastic discrete-time optimal control problems for interacting agents. Extending previous deterministic results, we show th…