Peer Reviewed Publications
E. Carlini, L. Saluzzi, High order Tensor-Train-Based Schemes for High-Dimensional Mean Field Games, accepted on SIAM Journal on Scientific Computing.
M. Sperl, L. Saluzzi, D. Kalise and L. Grune, Separable Approximations of Optimal Value Functions and Their Representation by Neural Networks, SIAM Journal on Control and Optimization, 64 (3), 1099-1126, 2026.
L. Saluzzi, The State-Dependent Riccati Equation in Nonlinear Optimal Control: Analysis, Error Estimation and Numerical Approximation, Journal of Optimization Theory and Applications, 209(1), 34, 2026.
L. Saluzzi, M. Strazzullo, Dynamical Low-Rank Approximation Strategies for Nonlinear Feedback Control Problems, Journal of Numerical Mathematics, 2025.
A. Alla, M. Berardi, and L. Saluzzi, State Dependent Riccati for dynamic boundary control
to optimize irrigation in Richards’ equation framework, Mathematics and Computers in
Simulation, 232, 261–275, 2025.
M. Oster, L. Saluzzi, and T. Wenzel, A comparison study of supervised learning techniques for the approximation of high dimensional functions and feedback control, Dynamic Games and Applications, 15(2), 454–480, 2025.
G. Kirsten and L. Saluzzi, A multilinear HJB-POD method for the optimal control of PDEs on a tree structure, Journal of Scientific Computing, 101 (2), 41, 2024.
S. Dolgov, D. Kalise, L. Saluzzi, Data-driven Tensor Train Gradient Cross Approximation for Hamilton-Jacobi-Bellman Equations, SIAM J. Sci. Comput., 45 (5), A2153-A2184, 2023.
M. Falcone, G. Kirsten, L. Saluzzi, Approximation of Optimal Control Problems for the Navier-Stokes equation via multilinear HJB-POD, Applied Mathematics and Computation, 442, 2023.
L. Saluzzi, A. Alla, M. Falcone, Error estimates for a tree structure algorithm solving finite horizon control problems, ESAIM: Control, Optimisation and Calculus of Variations, 28 (69) 2022.
A. Alla, M. Falcone, L.Saluzzi, A tree structure algorithm for optimal control problems with state constraints, Rendiconti di Matematica e delle sue Applicazioni, 41: 193-221, 2020.
A. Alla, L. Saluzzi, A HJB-POD approach for the control of nonlinear PDEs on a tree structure, Applied Numerical Mathematics, 155: 192-207, 2020.
A. Alla, M. Falcone, L. Saluzzi, An efficient DP algorithm on a tree-structure for finite horizon optimal control problems, SIAM J. Sci. Comput., 41 (4), A2384–A2406 , 2019.
A. Alla, M. Falcone, L. Saluzzi, An efficient DP algorithm on a tree-structure for finite horizon optimal control problems, SIAM J. Sci. Comput., 41 (4), A2384–A2406 , 2019.
Submitted Papers
S. Dolgov, D. Kalise, and L. Saluzzi, Statistical Proper Orthogonal Decomposition for model reduction in feedback control, 2024.
S. Massei, L. Saluzzi , On the data-sparsity of the solution of Riccati equations with applications to feedback control, 2024.
Peer Reviewed Conference Proceedings
M Sperl, L Saluzzi, L Grüne, and D Kalise, Separable approximations of optimal value functions under a decaying sensitivity assumption, IEEE Conference on Decision and Control, 2024
A. Alla, L. Saluzzi, Feedback reconstruction techniques for optimal control problems on a tree structure, ECCOMAS Congress 2022.
S.Dolgov, D. Kalise, L. Saluzzi, Optimizing semilinear representations for State-dependent Riccati Equation-based feedback control, in Conference Proceedings of the 25th IFAC Symposium on Mathematical Theory of Networks and Systems MTNS 2022, 55 (30), 510-515, 2022.
A. Alla, M. Falcone, L. Saluzzi, High-order Approximation of the Finite Horizon Control Problem via a Tree Structure Algorithm, in Conference Proceedings of the 3rd IFAC Conference on Control of Systems Governed by Partial Differential Equations, 52 (2), 19-24, 2019.
Phd Thesis