Danilo Macciò
Orcid: 0000-0002-2627-4953
According to our database1,
Danilo Macciò
authored at least 36 papers
between 2006 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Model Predictive Control of Port-City Traffic Interactions Over Shared Urban Infrastructure.
IEEE Trans. Control. Syst. Technol., March, 2024
2023
An imitation learning approach for the control of a low-cost low-accuracy robotic arm for unstructured environments.
Int. J. Intell. Robotics Appl., March, 2023
2022
Improving the variability of urban traffic microsimulation through the calibration of generative parameter models.
J. Intell. Transp. Syst., 2022
Echo state network ensembles for surrogate models with an application to urban mobility.
Proceedings of the International Joint Conference on Neural Networks, 2022
2021
Deep Learning and Low-discrepancy Sampling for Surrogate Modeling with an Application to Urban Traffic Simulation.
Proceedings of the International Joint Conference on Neural Networks, 2021
Proceedings of the International Joint Conference on Neural Networks, 2021
2020
Pattern Recognit., 2020
Learning Robustly Stabilizing Explicit Model Predictive Controllers: A Non-Regular Sampling Approach.
IEEE Control. Syst. Lett., 2020
2019
An Improved Load Flow Method for MV Networks Based on LV Load Measurements and Estimations.
IEEE Trans. Instrum. Meas., 2019
2018
IEEE Trans. Neural Networks Learn. Syst., 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
2017
A Novel Approach for Sampling in Approximate Dynamic Programming Based on F-Discrepancy.
IEEE Trans. Cybern., 2017
IEEE Trans. Cybern., 2017
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017
2016
Low-Discrepancy Points for Deterministic Assignment of Hidden Weights in Extreme Learning Machines.
IEEE Trans. Neural Networks Learn. Syst., 2016
IEEE Trans. Cybern., 2016
2015
Efficient use of Nadaraya-Watson models and low-discrepancy sequences for approximate dynamic programming.
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
Proceedings of the 2015 International Joint Conference on Neural Networks, 2015
2014
Local Linear Regression for Function Learning: An Analysis Based on Sample Discrepancy.
IEEE Trans. Neural Networks Learn. Syst., 2014
Low-discrepancy sampling for approximate dynamic programming with local approximators.
Comput. Oper. Res., 2014
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
An approach to exploit non-optimized data for efficient control of unknown systems through neural and kernel models.
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
Proceedings of the 2014 International Joint Conference on Neural Networks, 2014
2013
IEEE Trans. Neural Networks Learn. Syst., 2013
Function learning with local linear regression models: An analysis based on discrepancy.
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
Proceedings of the 2013 International Joint Conference on Neural Networks, 2013
2012
Neurocomputing, 2012
Expert Syst. Appl., 2012
2011
J. Multivar. Anal., 2011
A comparison of global and semi-local approximation in T-stage stochastic optimization.
Eur. J. Oper. Res., 2011
2010
Neural Networks, 2010
2008
IEEE Trans. Neural Networks, 2008
2006
Design of Parameterized State Observers and Controllers for a Class of Nonlinear Continuous-Time Systems.
Proceedings of the 45th IEEE Conference on Decision and Control, 2006