5 citations · 6 across the 8 of their papers we have counts for
14 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…
The turnpike property for high-dimensional interacting agent systems in discrete time
Martin Gugat, Michael Herty, Jiehong Liu +1
We investigate the interior turnpike phenomenon for discrete-time multi-agent optimal control problems. While for continuous systems the turnpike property has been established, we…
Controllability of continuous networks and a kernel-based learning approximation
Michael Herty, Chiara Segala, Giuseppe Visconti
Residual deep neural networks are formulated as interacting particle systems leading to a description through neural differential equations, and, in the case of large input data, t…
Data/moment-driven approaches for fast predictive control of collective dynamics
Giacomo Albi, Sara Bicego, Michael Herty +3
Feedback control synthesis for large-scale particle systems is reviewed in the framework of model predictive control (MPC). The high-dimensional character of collective dynamics ha…
Reproducing kernel Hilbert spaces in the mean field limit
Christian Fiedler, Michael Herty, Michael Rom +2
Kernel methods, being supported by a well-developed theory and coming with efficient algorithms, are among the most popular and successful machine learning techniques. From a mathe…
The turnpike property for mean-field optimal control problems
Martin Gugat, Michael Herty, Chiara Segala
We study the turnpike phenomenon for optimal control problems with mean field dynamics that are obtained as the limit of systems governed by a large number $N…
Robust feedback stabilization of interacting multi-agent systems under uncertainty
Giacomo Albi, Michael Herty, Chiara Segala
We consider control strategies for large-scale interacting agent systems under uncertainty. The particular focus is on the design of robust controls that allow to bound the varianc…
Optimized leaders strategies for crowd evacuation in unknown environments with multiple exits
Giacomo Albi, Federica Ferrarese, Chiara Segala
In this chapter, we discuss the mathematical modeling of egressing pedestrians in an unknown environment with multiple exits. We investigate different control problems to enhance t…
Moment-Driven Predictive Control of Mean-Field Collective Dynamics
G. Albi, M. Herty, D. Kalise +1
The synthesis of control laws for interacting agent-based dynamics and their mean-field limit is studied. A linearization-based approach is used for the computation of sub-optimal…
Autoregressive approaches to import--export time series II: a concrete case study
Luca Di Persio, Chiara Segala
The present work constitutes the second part of a two-paper project that, in particular, deals with an in-depth study of effective techniques used in econometrics in order to make…