Zobrazeno 1 - 10
of 27
pro vyhledávání: '"Daniela Selvi"'
Autor:
null Raffaele Bolla, null Riccardo Trivisonno, null Carla Raffaelli, null Franco Davoli, null Walter Cerroni, null Roberto Bruschi, null Daniela Selvi, null Chiara Lombardo, null Gianluca Davoli, null Davide Borsatti
Publikováno v:
ITU Journal on Future and Evolving Technologies. 3:589-601
Factory automation in the context of Industry 4.0/5.0 requires safety levels to satisfy more stringent and tight limits than those available so far. This goal is further challenged by the extension to the wireless environment of industrial shop floor
Publikováno v:
2022 European Control Conference (ECC).
Publikováno v:
Machine Learning. 110:1549-1584
This work belongs to the strand of literature that combines machine learning, optimization, and econometrics. The aim is to optimize the data collection process in a specific statistical model, commonly used in econometrics, employing an optimization
Publikováno v:
European Journal of Control. 59:175-187
For model-free optimal control design, this paper proposes an approach based on optimizing the reference model that is used in direct data-driven controller synthesis. Optimality is defined with respect to suitable cost functions reflecting desired p
Publikováno v:
Soft Computing. 24:15937-15949
This paper is focused on the unbalanced fixed effects panel data model. This is a linear regression model able to represent unobserved heterogeneity in the data, by allowing each two distinct observational units to have possibly different numbers of
Autor:
Davide Borsatti, Gianluca Davoli, Chiara Lombardo, Daniela Selvi, Roberto Bruschi, Walter Cerroni, Franco Davoli, Carla Raffaelli, Riccardo Trivisonno, Raffaele Bolla
Publikováno v:
2022 18th International Conference on the Design of Reliable Communication Networks (DRCN).
Publikováno v:
High-Dimensional Optimization and Probability ISBN: 9783031008313
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e34af94c624deeceabe5d5b5cdf99421
https://doi.org/10.1007/978-3-031-00832-0_7
https://doi.org/10.1007/978-3-031-00832-0_7
A promising technique for the spectral design of acoustic metamaterials is based on the formulation of suitable constrained nonlinear optimization problems. Unfortunately, the straightforward application of classical gradient-based iterative optimiza
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d85632f49b19abeca2ee8baa2698c02
http://arxiv.org/abs/2104.02588
http://arxiv.org/abs/2104.02588
Autor:
Benedetto Allotta, Andrea Rindi, Daniela Selvi, Luigi Rucher, Enrico Meli, Alessandro Capuozzo
The problem of vehicle autonomous driving currently represents a topic of great interest from both theoretical and practical points of view. Among the challenging tasks to be addressed within any autonomous driving framework, one of the most importan
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e810baa71e3ef227d53895f51d252c70
http://hdl.handle.net/2158/1257743
http://hdl.handle.net/2158/1257743
Autor:
Daniela Selvi, Giorgio Gnecco
Publikováno v:
IEEE Control Systems Letters. 2:549-554
In this letter, a formulation of Fermat’s principle as an optimization problem over a finite number of stages is used to prove strong convexity and smoothness of the solutions to certain geometric optics problems. The class of problems considered i