Luca Saluzzi
Orcid: 0000-0002-3018-6948
According to our database1,
Luca Saluzzi
authored at least 15 papers
between 2019 and 2025.
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Bibliography
2025
A Comparison Study of Supervised Learning Techniques for the Approximation of High Dimensional Functions and Feedback Control.
Dyn. Games Appl., May, 2025
The State-Dependent Riccati Equation in Nonlinear Optimal Control: Analysis, Error Estimation and Numerical Approximation.
CoRR, March, 2025
CoRR, January, 2025
State Dependent Riccati for dynamic boundary control to optimize irrigation in Richards' equation framework.
Math. Comput. Simul., 2025
2024
J. Sci. Comput., November, 2024
On the data-sparsity of the solution of Riccati equations with applications to feedback control.
CoRR, 2024
2023
Data-Driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations.
SIAM J. Sci. Comput., October, 2023
CoRR, 2023
Approximation of optimal control problems for the Navier-Stokes equation via multilinear HJB-POD.
Appl. Math. Comput., 2023
Separable Approximations of Optimal Value Functions Under a Decaying Sensitivity Assumption.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
CoRR, 2022
Optimizing semilinear representations for State-dependent Riccati Equation-based feedback control.
CoRR, 2022
2020
CoRR, 2020
2019
An Efficient DP Algorithm on a Tree-Structure for Finite Horizon Optimal Control Problems.
SIAM J. Sci. Comput., 2019