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Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement.

D. Caporale, L. Deori, R. Mura, A. Falsone, R. Vignali, L. Giulioni, M. Pirotta, and G. Manganini. ECC, page 1420-1425. IEEE, (2015)

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Matteo Garavoglia

Matteo Bertini

Matteo Gabba

Marco Matteo

Matteo Rini

Other publications of authors with the same name

Efficient Bias-Span-Constrained Exploration-Exploitation in Reinforcement Learning.R. Fruit, M. Pirotta, A. Lazaric, and R. Ortner. ICML, volume 80 of Proceedings of Machine Learning Research, page 1573-1581. PMLR, (2018)Stochastic Variance-Reduced Policy Gradient.M. Papini, D. Binaghi, G. Canonaco, M. Pirotta, and M. Restelli. ICML, volume 80 of Proceedings of Machine Learning Research, page 4023-4032. PMLR, (2018)No-Regret Exploration in Goal-Oriented Reinforcement Learning.J. Tarbouriech, E. Garcelon, M. Valko, M. Pirotta, and A. Lazaric. CoRR, (2019)Inverse Reinforcement Learning through Policy Gradient Minimization.M. Pirotta, and M. Restelli. AAAI, page 1993-1999. AAAI Press, (2016)Reinforcement Learning in Linear MDPs: Constant Regret and Representation Selection.M. Papini, A. Tirinzoni, A. Pacchiano, M. Restelli, A. Lazaric, and M. Pirotta. NeurIPS, page 16371-16383. (2021)Leveraging Good Representations in Linear Contextual Bandits.M. Papini, A. Tirinzoni, M. Restelli, A. Lazaric, and M. Pirotta. ICML, volume 139 of Proceedings of Machine Learning Research, page 8371-8380. PMLR, (2021)On the Complexity of Representation Learning in Contextual Linear Bandits.A. Tirinzoni, M. Pirotta, and A. Lazaric. AISTATS, volume 206 of Proceedings of Machine Learning Research, page 7871-7896. PMLR, (2023)A Unified Framework for Conservative Exploration.Y. Yang, T. Wu, H. Zhong, E. Garcelon, M. Pirotta, A. Lazaric, L. Wang, and S. Du. CoRR, (2021)Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems.C. D'Eramo, A. Nuara, M. Pirotta, and M. Restelli. AAAI, page 1840-1846. AAAI Press, (2017)Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement.D. Caporale, L. Deori, R. Mura, A. Falsone, R. Vignali, L. Giulioni, M. Pirotta, and G. Manganini. ECC, page 1420-1425. IEEE, (2015)

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Disambiguation of "Pirotta, Matteo"

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Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement.

Please choose a person to relate this publication to

Matteo Garavoglia

Matteo Bertini

Matteo Gabba

Marco Matteo

Matteo Rini

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Pirotta, Matteo"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement.

Please choose a person to relate this publication to

Matteo Garavoglia

Matteo Bertini

Matteo Gabba

Marco Matteo

Matteo Rini

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Optimal control to reduce emissions in gasoline engines: an iterative learning control approach for ECU calibration maps improvement.