Algo Carè

Welcome to the homepage of

Algo Carè

Dept. of Information Engineering
University of Brescia
via Branze, 38
25123 Brescia
ITALY

e-mail: algo.care (at) unibs.it

Past Positions

Research Fellow at
The University of Melbourne

Department of Electrical and Electronic Engineering
Melbourne School of Engineering

ERCIM Fellow at

EMI - Engineering and Management Intelligence Laboratory,
SZTAKI - Institute for Computer Science and Control,
MTA - Hungarian Academy of Sciences

ERCIM Fellow at

CWI logo

CWI - Centrum Wiskunde & Informatica
(National Research Institute for Mathematics and Computer Science)

RESEARCH TOPICS

Scenario Approach
System Identification
Learning Theory
Model Selection

PEOPLE

        Marco C. Campi - University of Brescia
        Simone Garatti - Politecnico di Milano
Erik Weyer - University of Melbourne
Balázs Csanád Csáji - SZTAKI
        Enrico Camporeale - CWI
Fabio Baronio- University of Brescia

Teaching (in Italian)

Blackboard caricature of me by an "anonymous" attendee of the Uncertain Dynamic System course.

(2020-2021) Sistemi Dinamici Incerti
(2019-2020) Sistemi Dinamici Incerti
(2018-2019) Sistemi Dinamici Incerti

Per qualunque richiesta di informazioni (su contenuti e modalità, sovrapposizione di orari, curiosità, etc. ),
scrivete senza esitazione a me o al Prof. Campi (si veda anche la pagina DETTAGLI_SUL_NUOVO_CORSO)

Link esterni a proposito del filtraggio alla Kalman:
This algorithm is key to space travel, GPS, VR and more, and it is over 50 years old
Applications of Kalman Filtering in Aerospace 1960 to the Present

Selected Publications

S. Garatti, M.C. Campi, A. Carè
“On a class of Interval Predictor Models with universal reliability,”
Automatica. 110, 108542 [doi: 10.1016/j.automatica.2019.108542], 2019
A. Carè, S. Garatti, M.C. Campi
“The wait-and-judge scenario approach applied to antenna array design,”
Computational Management Science. 16:481-499 [doi: 10.1007/s10287-019-00345-5], 2019
H.A. Nasir A. Carè, E. Weyer
“A Scenario-Based Stochastic MPC Approach for Problems With Normal and Rare Operations With an Application to Rivers,”
IEEE Transactions on Control Systems Technology. 27(4):1397-1410 [doi: 10.1109/TCST.2018.2811404], 2019
A. Carè, F.A. Ramponi, M.C. Campi
“A new classification algorithm with guaranteed sensitivity and specificity for medical applications,”
IEEE Control Systems Letters. 2(3):393-398 [doi: 10.1109/LCSYS.2018.2840427], 2018
[for code, more reserach and info on the topic of CLASSIFICATION click here]
A. Carè, B.Cs. Csáji, M.C. Campi, E. Weyer
“Finite-Sample System Identification: An Overview and a New Correlation Method,”
IEEE Control Systems Letters. 2(1):61-66 [doi: 10.1109/LCSYS.2017.2720969], 2017
A. Carè, S. Garatti, M.C. Campi
“A Coverage Theory for Least Squares,”
Journal of the Royal Statistical Society: Series B (Statistical Methodology), online-first [doi: 10.1111/rssb.12219], 2016
authors' self-archived copy (personal use),
supplementary material
A. Carè, S. Garatti, M.C. Campi
“Scenario min-max optimization and the risk of empirical costs,”
SIAM Journal on Optimization. 25(4):2061-2080, 2015
*** Winner of the triennial Stochastic Programming Society Student Paper Prize 2016 (received during the XIV ICSP) ***
A. Carè, S. Garatti, M.C. Campi
“FAST-Fast Algorithm for the Scenario Technique,”
Operations Research. 62(3):662-671. 2014
M.C. Campi, A. Carè
“Random convex programs with L1-regularization: Sparsity and generalization,”
SIAM Journal on Control and Optimization. 51(5):3532-3557. 2013

(see also my Google Scholar Profile)

Book Chapter

A. Carè, E. Camporeale (2018)
Regression, in Machine Learning Techniques for Space Weather (Elsevier)
[doi: 10.1016/B978-0-12-811788-0.00004-4]

Some presentations slides

14^th International Conference on Stochastic Programming (Búzios, Brazil, 2016)
"Scenario Min-Max Optimization and the Risk of Empirical Costs" - Slides
(XIV ICSP)

Ph.D. Thesis presentation (12 Marzo 2013)
"Data-Based Optimization for Applications to Decision-Making, Identification and Control - A Study of Coverage Properties" - Slides (in Italian)
Link to the Ph.D. Thesis.

18^th IFAC World Congress (Milan, Italy, 2011)
Presentation of the paper:
"FAST: an algorithm for the scenario approach with reduced sample complexity" - Slides

S.I.D.R.A. Conference 2010 (L'Aquila, Italy, 13-15 September 2010)
Data-driven optimization through the scenario approach - Slides

Seminar (16 May 2012, 30 May 2011, 18 June 2009) - Master Thesis Presentation (26 March 2009)
Un nuovo algoritmo per costruzione di classificatori da dati sperimentali con errore di generalizzazione garantito - Slides (in Italian): 2009, 2011, 2012
Link to the Master Thesis

Miscellanea

Slides of a short and definitely non-specialist talk on Cantor's theory of the infinite (2011).