Zobrazeno 1 - 10
of 210
pro vyhledávání: '"Giuseppe Carlo Calafiore"'
Publikováno v:
PLoS ONE, Vol 17, Iss 2 (2022)
The COVID-19 pandemic is bringing disruptive effects on the healthcare systems, economy and social life of countries all over the world. Even though the elder portion of the population is the most severely affected by the COVID-19 disease, the counte
Externí odkaz:
https://doaj.org/article/2b134e38335643cc9646822ab302ed1e
Publikováno v:
International Journal of Robust and Nonlinear Control, 33(9), 4808-4823. Wiley
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control
The COVID-19 pandemic has led to the unprecedented challenge of devising massive vaccination rollouts, toward slowing down and eventually extinguishing the diffusion of the virus. The two-dose vaccination procedure, speed requirements, and the scarci
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::be2874a6bfc80218432708e0cb268f73
https://research.rug.nl/en/publications/5bf412d2-0be4-443f-8a53-8d70e4b6a613
https://research.rug.nl/en/publications/5bf412d2-0be4-443f-8a53-8d70e4b6a613
Publikováno v:
European Journal of Operational Research, 304(3), 1269-1278. ELSEVIER SCIENCE BV
The ongoing COVID-19 pandemic has led public health authorities to face the unprecedented challenge of planning a global vaccination campaign, which for most protocols entails the administration of two doses, separated by a bounded but flexible time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26ff93cfed3f65b3363b6f6cab72fb16
https://research.rug.nl/en/publications/61d9c9bc-6de7-4189-b9ca-fb36df75e390
https://research.rug.nl/en/publications/61d9c9bc-6de7-4189-b9ca-fb36df75e390
Publikováno v:
IEEE transactions on automatic control
(2021). doi:10.1109/TAC.2021.3056398
info:cnr-pdr/source/autori:Possieri, Corrado; Incremona, Gian Paolo; Calafiore, Giuseppe C.; Ferrara, Antonella/titolo:An Iterative Data-Driven Linear Quadratic Method to Solve Nonlinear Discrete-Time Tracking Problems/doi:10.1109%2FTAC.2021.3056398/rivista:IEEE transactions on automatic control (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
(2021). doi:10.1109/TAC.2021.3056398
info:cnr-pdr/source/autori:Possieri, Corrado; Incremona, Gian Paolo; Calafiore, Giuseppe C.; Ferrara, Antonella/titolo:An Iterative Data-Driven Linear Quadratic Method to Solve Nonlinear Discrete-Time Tracking Problems/doi:10.1109%2FTAC.2021.3056398/rivista:IEEE transactions on automatic control (Print)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
The objective of this note is to introduce a novel data-driven iterative linear quadratic control method for solving a class of nonlinear optimal tracking problems. Specifically, an algorithm is proposed to approximate the Q-factors arising from line
Autor:
Alessandro Zanco, Pedro Toledo, Stefano Grivet-Talocia, Giuseppe Carlo Calafiore, Paolo Stefano Crovetti, Anton V. Proskurnikov, Tommaso Bradde
Publikováno v:
IEEE Transactions on Components, Packaging and Manufacturing Technology. 11:1355-1368
This article proposes a black-box behavioral modeling framework for analog circuit blocks (CBs) operating under small-signal conditions around nonstationary operating points. Such variations may be induced either by changes in the loading conditions
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems 32 (2021): 3274–3281. doi:10.1109/TNNLS.2020.3010304
info:cnr-pdr/source/autori:Calafiore, Giuseppe C.; Possieri, Corrado/titolo:Output Feedback Q-Learning for Linear-Quadratic Discrete-Time Finite-Horizon Control Problems/doi:10.1109%2FTNNLS.2020.3010304/rivista:IEEE Transactions on Neural Networks and Learning Systems/anno:2021/pagina_da:3274/pagina_a:3281/intervallo_pagine:3274–3281/volume:32
info:cnr-pdr/source/autori:Calafiore, Giuseppe C.; Possieri, Corrado/titolo:Output Feedback Q-Learning for Linear-Quadratic Discrete-Time Finite-Horizon Control Problems/doi:10.1109%2FTNNLS.2020.3010304/rivista:IEEE Transactions on Neural Networks and Learning Systems/anno:2021/pagina_da:3274/pagina_a:3281/intervallo_pagine:3274–3281/volume:32
An algorithm is proposed to determine output feedback policies that solve finite-horizon linear-quadratic (LQ) optimal control problems without requiring knowledge of the system dynamical matrices. To reach this goal, the $Q$ -factors arising from fi
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-6
In this article, we propose an efficient multiclass classification scheme based on sparse centroids classifiers. The proposed strategy exhibits linear complexity with respect to both the number of classes and the cardinality of the feature space. The
Autor:
Giuseppe Carlo Calafiore, Marisa Hillary Morales, Serge Marquie, Vittorio Tiozzo, Giulia Fracastoro
Publikováno v:
IFAC-PapersOnLine. 53:16983-16988
Within the Private Equity (PE) market, the event of a private company undertaking an Initial Public Offering (IPO) is usually a very high-return one for the investors in the company. For this reason, an effective predictive model for the IPO event is
Publikováno v:
IFAC-PapersOnLine. 53:518-523
The nearest-centroid classifier is a simple linear-time classifier based on computing the centroids of the data classes in the training phase, and then assigning a new datum to the class corresponding to its nearest centroid. Thanks to its very low c
Publikováno v:
International journal of control
(2020). doi:10.1080/00207179.2020.1782476
info:cnr-pdr/source/autori:Calafiore, Giuseppe C.; Novara, Carlo; Possieri, Corrado/titolo:Control analysis and design via randomised coordinate polynomial minimisation/doi:10.1080%2F00207179.2020.1782476/rivista:International journal of control (Print)/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume
(2020). doi:10.1080/00207179.2020.1782476
info:cnr-pdr/source/autori:Calafiore, Giuseppe C.; Novara, Carlo; Possieri, Corrado/titolo:Control analysis and design via randomised coordinate polynomial minimisation/doi:10.1080%2F00207179.2020.1782476/rivista:International journal of control (Print)/anno:2020/pagina_da:/pagina_a:/intervallo_pagine:/volume
A relevant family of control analysis and design problems can be reduced to the minimisation of a multivariate polynomial objective over a semialgebraic set. Such control problem formulations, however, are nonconvex in general and hard to solve in pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89768dcebd41a7a01b7fa6771c0ba8d4
http://hdl.handle.net/2108/294494
http://hdl.handle.net/2108/294494