Fabio Pasqualetti

Journal Articles

T. Guo and A. A. Al Makdah and V. Krishnan and F. Pasqualetti, Imitation and Transfer Learning for LQG Control. IEEE Control Systems Letters, 7:2149-2154, 2023.
A. A. Al Makdah and F. Pasqualetti, Model-based and Data-based Dynamic Output Feedback for Externally Positive Systems. IEEE Transactions on Automatic Control, 2023. Submitted.
A. A. Al Makdah and V. Krishnan and F. Pasqualetti, Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness. IEEE Open Journal of Control Systems, 1:85-99, 2022.
A. A. Al Makdah and V. Katewa and F. Pasqualetti, A Fundamental Performance Limitation for Adversarial Classification. IEEE Control Systems Letters, 4(1):169-174, 2019. [PDF]

A. A. Al Makdah and F. Pasqualetti, On the Sample Complexity of the Linear Quadratic Gaussian Regulator. IEEE Conf. on Decision and Control, Marina Bay Sands, Singapore, December 2023. To appear.
A. A. Al Makdah and V. Krishnan and V. Katewa and F. Pasqualetti, Behavioral Feedback for Optimal LQG Control. IEEE Conf. on Decision and Control, Cancún, Mexico, pages 4660-4666, December 2022. [PDF]
A. A. Al Makdah and V. Katewa and F. Pasqualetti, Robust Adversarial Classification via Abstaining. IEEE Conf. on Decision and Control, Austin, TX, pages 763-768, December 2021.
A. A. Al Makdah and V. Katewa and F. Pasqualetti, Accuracy Prevents Robustness in Perception-based Control. American Control Conference, Denver, CO, USA, July 2020. [PDF]
R. Anguluri and A. A. Al Makdah and V. Katewa and F. Pasqualetti, On the Robustness of Data-Driven Controllers for Linear Systems. Learning for Dynamics & Control, San Francisco, CA, USA, pages 404-412, June 2020. [PDF]
V. Krishnan and A. A. Al Makdah and F. Pasqualetti, Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing. Advances in Neural Information Processing Systems, Vancouver, Canada, pages 10924-10935, December 2020. [PDF]