Algo Carè

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Marco C. CampiUniversity of Brescia, professorVerified email at unibs.it
Simone GarattiPolitecnico di Milano - Dipartimento di Elettronica, Informazione e BioingegneriaVerified email at polimi.it
Erik WeyerThe University of MelbourneVerified email at unimelb.edu.au
Balázs Csanád CsájiSZTAKI: Institute for Computer Science and Control, Budapest, HungaryVerified email at sztaki.hu
Enrico CamporealeUniversity of Colorado, BoulderVerified email at noaa.gov
Hasan Arshad NasirAssistant Professor, National University of Sciences and Technology, IslamabadVerified email at seecs.edu.pk
Gianluigi PillonettoProfessor of Automatic Control, University of PadovaVerified email at dei.unipd.it
Sergio Matteo Savaresipolitecnico milanoVerified email at polimi.it
Anupam A. ThatteSr. R&D Engineer, MISOVerified email at tamu.edu
P. R. KumarTexas A&M UniversityVerified email at tamu.edu
Simone FormentinAssociate Professor, Politecnico di MilanoVerified email at polimi.it
Le XieSegers Family Dean’s Excellence Professor in Engineering, Texas A&M UniversityVerified email at tamu.edu
M. Sadegh ModarresiERCOTVerified email at ercot.com
Roy CobbenhagenUniversity Researcher Eindhoven University of TechnologyVerified email at tue.nl
Fabio BaronioUniversità degli Studi di BresciaVerified email at ing.unibs.it
QJ WangUniversity of MelbourneVerified email at unimelb.edu.au
Tongtiegang Zhao (Tony)Sun Yat-Sen University; UniMelb; CSIRO; TsinghuaVerified email at mail.sysu.edu.cn
Maurice HeemelsFull Professor Eindhoven University of TechnologyVerified email at tue.nl
Laszlo GerencserInstitute for Computer Science and ControlVerified email at sztaki.hu
Balázs GerencsérAlfréd Rényi Institute of MathematicsVerified email at renyi.mta.hu

Algo Carè

University of Brescia, Italy

Verified email at unibs.it - Homepage

systems and control system identification randomised algorithms statistical learning


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Deterministic continuous-time Virtual Reference Feedback Tuning (VRFT) with application to PID design S Formentin, MC Campi, A Carè, SM Savaresi Systems & Control Letters 127, 25-34, 2019	77	2019
Scenario min-max optimization and the risk of empirical costs A Carè, S Garatti, MC Campi SIAM Journal on Optimization 25 (4), 2061-2080, 2015	68	2015
Classification of solar wind with machine learning E Camporeale, A Carè, JE Borovsky Journal of Geophysical Research: Space Physics 122 (11), 10,910-10,920, 2017	67	2017
Scenario-based economic dispatch with tunable risk levels in high-renewable power systems MS Modarresi, L Xie, MC Campi, S Garatti, A Care, AA Thatte, PR Kumar IEEE Transactions on Power Systems 34 (6), 5103-5114, 2018	65	2018
Finite-sample system identification: An overview and a new correlation method A Care, BC Csáji, MC Campi, E Weyer IEEE Control Systems Letters 2 (1), 61-66, 2017	64	2017
FAST—Fast algorithm for the scenario technique A Carè, S Garatti, MC Campi Operations Research 62 (3), 662-671, 2014	62	2014
Random Convex Programs with -Regularization: Sparsity and Generalization MC Campi, A Caré SIAM Journal on Control and Optimization 51 (5), 3532-3557, 2013	54	2013
A toolbox for virtual reference feedback tuning (VRFT) A Care, F Torricelli, MC Campi, SM Savaresi 2019 18th European control conference (ECC), 4252-4257, 2019	32	2019
A new classification algorithm with guaranteed sensitivity and specificity for medical applications A Care, FA Ramponi, MC Campi IEEE Control Systems Letters 2 (3), 393-398, 2018	26	2018
On a class of interval predictor models with universal reliability S Garatti, MC Campi, A Care Automatica 110, 108542, 2019	23	2019
The scenario approach: A tool at the service of data-driven decision making MC Campi, A Carè, S Garatti Annual Reviews in Control 52, 1-17, 2021	22	2021
A scenario-based stochastic MPC approach for problems with normal and rare operations with an application to rivers HA Nasir, A Carè, E Weyer IEEE Transactions on Control Systems Technology 27 (4), 1397-1410, 2018	16	2018
A coverage theory for least squares A Care, S Garatti, MC Campi Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2017	13	2017
Sign-perturbed sums (SPS) with instrumental variables for the identification of ARX systems V Volpe, BC Csáji, A Care, E Weyer, MC Campi 2015 54th IEEE Conference on Decision and Control (CDC), 2115-2120, 2015	13	2015
Efficient river management using stochastic MPC and ensemble forecast of uncertain in-flows HA Nasir, T Zhao, A Care, QJ Wang, E Weyer IFAC-PapersOnLine 51 (5), 37-42, 2018	12	2018
Kernel-based SPS G Pillonetto, A Carè, MC Campi IFAC-PapersOnLine 51 (15), 31-36, 2018	11	2018
Facing undermodelling in Sign-Perturbed-Sums system identification A Carè, MC Campi, BC Csáji, E Weyer Systems & Control Letters 153, 104936, 2021	10	2021
The wait-and-judge scenario approach applied to antenna array design A Carè, S Garatti, MC Campi Computational Management Science 16 (3), 481-499, 2019	9	2019
ACCRUE: Accurate and Reliable Uncertainty Estimate in Deterministic models E Camporeale, A Carè International Journal for Uncertainty Quantification 11 (4), 81-94, 2021	8	2021
A randomised approach to flood control using Value-at-Risk HA Nasir, A Carè, E Weyer 2015 54th IEEE Conference on Decision and Control (CDC), 3939-3944, 2015	8	2015

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