Anna Scampicchio

Orcid: 0000-0002-2238-6341

According to our database1, Anna Scampicchio authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Active Learning-Based Model Predictive Coverage Control.
IEEE Trans. Autom. Control., September, 2024

Data-driven control of input-affine systems: the role of the signature transform.
CoRR, 2024

Inverse optimal control as an errors-in-variables problem.
Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

2023
Bayesian Multi-Task Learning MPC for Robotic Mobile Manipulation.
IEEE Robotics Autom. Lett., June, 2023

Kernel-based learning of orthogonal functions.
Neurocomputing, 2023

Error Analysis of Regularized Trigonometric Linear Regression With Unbounded Sampling: A Statistical Learning Viewpoint.
IEEE Control. Syst. Lett., 2023

On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics.
Proceedings of the International Joint Conference on Neural Networks, 2023

2022
Sample Complexity and Minimax Properties of Exponentially Stable Regularized Estimators.
IEEE Trans. Autom. Control., 2022

Bayesian frequentist bounds for machine learning and system identification.
Autom., 2022

An update-and-design scheme for scenario-based LQR synthesis.
Proceedings of the American Control Conference, 2022

2021
Stable and robust LQR design via scenario approach.
Autom., 2021

Bayesian multi-task learning using finite-dimensional models: A comparative study.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020
A convex approach to robust LQR.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020

2019
Bayesian Kernel-Based Linear Control Design.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

2018
A New Model Selection Approach to Hybrid Kernel-Based Estimation.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018


  Loading...