A majority voting classifier with probabilistic guarantees. - Giorgio Manganini; Alessandro Falsone; Maria Prandini (CCA, 2015)

A classification-based approach to the optimal control of affine switched systems. - Giorgio Manganini; Luigi Piroddi; Maria Prandini (CDC, 2015)

Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement. - Danilo Caporale; Luca Deori; Roberto Mura; Alessandro Falsone; Riccardo Vignali; Luca Giulioni; Matteo Pirotta; Giorgio Manganini (ECC, 2015)

Following Newton direction in Policy Gradient with parameter exploration. - Giorgio Manganini; Matteo Pirotta; Marcello Restelli; Luca Bascetta (IJCNN, 2015)

Policy Search for the Optimal Control of Markov Decision Processes: A Novel Particle-Based Iterative Scheme. - Giorgio Manganini; Matteo Pirotta; Marcello Restelli; Luigi Piroddi; Maria Prandini (IEEE Trans. Cybern., 2016)

Optimal control of large scale stochastic hybrid systems with a finite control space. - Giorgio Manganini (2016)

A data-based approach to power capacity optimization. - Giorgio Manganini; Alessandro Falsone; Jan Siroky; Maria Prandini (CDC, 2017)

A graph-based optimization framework for the Energy Management of District Systems. - Giorgio Manganini; Stefano Riverso; Konstantinos I. Kouramas (CDC, 2019)

Resource Aware Multifidelity Active Learning for Efficient Optimization. - Francesco Grassi; Giorgio Manganini; Michele Garraffa; Laura Mainini (CoRR, 2020)

Newton-based Policy Search for Networked Multi-agent Reinforcement Learning. - Giorgio Manganini; Simone Fioravanti; Giorgia Ramponi (CDC, 2022)

Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning. - Angelo Damiani; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (ICML, 2022)

pactus: A Python framework for trajectory classification. - Gustavo Viera-López; Jorge J. Morgado-Vega; Alfredo Reyes; Ernesto Altshuler; Yudivián Almeida-Cruz; Giorgio Manganini (J. Open Source Softw., 2023)

Transfer Learning for Dynamical Systems Models via Autoencoders and GANs. - Angelo Damiani; Gustavo Viera-López; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (ACC, 2024)

Policy Gradient with Active Importance Sampling. - Matteo Papini; Giorgio Manganini; Alberto Maria Metelli; Marcello Restelli (RLJ, 2024)

Improving trajectory classification through Kramers-Moyal coefficients. - Gustavo Viera-López; Jorge J. Morgado-Vega; Alfredo Reyes; Ernesto Altshuler; Yudivián Almeida-Cruz; Giorgio Manganini (AI Open, 2024)

Graph-based Data Mining, Pattern Recognition and Anomaly Detection for Intelligent Energy Networks. - Francesco Grassi; Giorgio Manganini; Konstantinos I. Kouramas (Comput. Ind. Eng., 2024)