Zobrazeno 1 - 10
of 310
pro vyhledávání: '"Marano, Stefano"'
Autor:
Braca, Paolo, Millefiori, Leonardo M., Aubry, Augusto, Marano, Stefano, De Maio, Antonio, Willett, Peter
We study the performance -- and specifically the rate at which the error probability converges to zero -- of Machine Learning (ML) classification techniques. Leveraging the theory of large deviations, we provide the mathematical conditions for a ML c
Externí odkaz:
http://arxiv.org/abs/2207.10939
Publikováno v:
IEEE Transactions on Signal Processing, vol. 69, pp. 5920-5934, 2021
Structured covariance matrix estimation in the presence of missing data is addressed in this paper with emphasis on radar signal processing applications. After a motivation of the study, the array model is specified and the problem of computing the m
Externí odkaz:
http://arxiv.org/abs/2105.03738
Autor:
Soldi, Giovanni, Forti, Nicola, Gaglione, Domenico, Braca, Paolo, Millefiori, Leonardo M., Marano, Stefano, Willett, Peter, Pattipati, Krishna
Publikováno v:
IEEE Communications Magazine, vol. 59, no. 9, pp. 16-22, 2021
The COVID-19 pandemic has, worldwide and up to December 2020, caused over 1.7 million deaths, and put the world's most advanced healthcare systems under heavy stress. In many countries, drastic restrictive measures adopted by political authorities, s
Externí odkaz:
http://arxiv.org/abs/2101.04620
Autor:
Marano, Stefano, Sayed, Ali H.
This work focuses on the development of a new family of decision-making algorithms for adaptation and learning, which are specifically tailored to decision problems and are constructed by building up on first principles from decision theory. A key ob
Externí odkaz:
http://arxiv.org/abs/2012.07844
Autor:
Braca, Paolo, Gaglione, Domenico, Marano, Stefano, Millefiori, Leonardo M., Willett, Peter, Pattipati, Krishna
During the course of an epidemic, one of the most challenging tasks for authorities is to decide what kind of restrictive measures to introduce and when these should be enforced. In order to take informed decisions in a fully rational manner, the ons
Externí odkaz:
http://arxiv.org/abs/2011.11540
Autor:
Braca, Paolo, Gaglione, Domenico, Marano, Stefano, Millefiori, Leonardo M., Willett, Peter, Pattipati, Krishna
This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. The decision statistic can be cast in a recursive form and is p
Externí odkaz:
http://arxiv.org/abs/2011.10502
Autor:
Millefiori, Leonardo M., Braca, Paolo, Zissis, Dimitris, Spiliopoulos, Giannis, Marano, Stefano, Willett, Peter K., Carniel, Sandro
Publikováno v:
Scientific Reports, vol. 11, 18039, 2021
To prevent the outbreak of the Coronavirus disease (COVID-19), many countries around the world went into lockdown and imposed unprecedented containment measures. These restrictions progressively produced changes to social behavior and global mobility
Externí odkaz:
http://arxiv.org/abs/2009.06960
Autor:
Marano, Stefano, Sayed, Ali H.
This paper studies the operation of multi-agent networks engaged in multi-task decision problems under the paradigm of simultaneous learning and adaptation. Two scenarios are considered: one in which a decision must be taken among multiple states of
Externí odkaz:
http://arxiv.org/abs/1912.05967
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Marano, Stefano, Willett, Peter
Emerging applications of sensor networks for detection sometimes suggest that classical problems ought be revisited under new assumptions. This is the case of binary hypothesis testing with independent - but not necessarily identically distributed -
Externí odkaz:
http://arxiv.org/abs/1810.07563