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Articles in Journals


S. Garatti, M.C. Campi

Non-convex scenario optimization

Matheamtical Programming, published online, 2024. https://doi.org/10.1007/s10107-024-02074-3

M.C. Campi, S. Garatti

Compression, Generalization and Learning.

Journal of Machine Learning Research, Vol. 24, 1-74, 2023.

S. Garatti, M.C. Campi

On Conditional Risk Assessments in Scenario Optimization.

SIAM Journal on Optimization, Vol. 33(2), 455-480, 2023.

M.C. Campi

Inductive knowledge under dominance.

Synthese, Vol. 201(6), article 184, 2023.

S. Garatti, A. Carč, M.C. Campi

Complexity is an effective observable to tune early stopping in scenario optimization.

IEEE Trans. on Automatic Control, Vol. 68(2), 928-942, 2023.
(DOI:
10.1109/TAC.2022.3153888)


M.C. Campi, A. Carč, S. Garatti.

The scenario approach: A tool at the service of data-driven decision making.
Annual Reviews in Control,  52, pp.1-17, 2021.

 

G. Arici, M.C. Campi, A. Carč, M. Dalai, F.A. Ramponi.

A Theory of the Risk for Empirical CVaR with Application to Portfolio Selection.
J. Syst. Sci. Complexity (special issue on occasion of the 60th birthday of Professor Lei Guo), vol. 34(5), 1879-1894, 2021.


M.C. Campi, S. Garatti
A Theory of the Risk for Optimization with Relaxation and its Application to Support Vector Machines.

Journal of Machine Learning Research 22 (288), 1-38, 2021.

 

A. Carč, M.C. Campi, E. Weyer.
State Conditional Filtering.
IEEE Trans. on Automatic Control, Vol. 67(7), 3381-3395.


A. Carč, M.C. Campi, B.C. Csaji, E. Weyer.
Facing undermodelling in Sign-Perturbed-Sums system identification.
Systems & Control Letters, vol. 153, 2021 (https://doi.org/10.1016/j.sysconle.2021.104936).

A.T.J.R. Cobbenhagen, A. Carč, M.C. Campi, F.A. Ramponi,  D.J. Antunes, W.P.M.H. Heemels
Novel bounds on the probability of misclassificaiton in majority voting: leveraging the majority size.
IEEE Control Systems Letters, vol. 5, issue 5, 1513 - 1518, 2020.

S. Garatti and M.C. Campi.
Risk and complexity in scenario optimization.
Mathematical Programming, 1-37, 2019.

S. Garatti, M.C. Campi, A. Carč,
On a Class of Interval Predictor Models with Universal Reliability.
Automatica,  110, pp.1-9, 2019.

S. Formentin, M.C. Campi, A. Carč, S.M. Savaresi.
Deterministic continuous-time Virtual Reference Feedback Tuning (VRFT) with application to PID design.

Systems & Control Letters, vol. 127, pp. 25-34, 2019.

S.Yu. Pilyugin, M.C. Campi.
Opinion formation in voting processes under bounded confidence.
Networks & Heterogeneous Media, vol. 14, no. 3, 617-632, 2019.

A. Carč, S. Garatti, M.C. Campi.
The wait-and-judge scenario approach applied to antenna array design.

Computational Management Science, vol.16, pp. 481-499, 2019.
 

M.S. Modarresi, Le Xie, M.C. Campi, S. Garatti, A. Carč, A.A. Thatte, P. R. Kumar. 

Scenario-based Economic Dispatch with Tunable Risk Levels in High-renewable Power Systems.
IEEE Trans. on Power Systems, Vol. 34(6), 5103-5114, 2019.
DOI:
10.1109/TPWRS.2018.2874464

A. Carč, F.A. Ramponi, M.C. Campi.
A new classification algorithm with guaranteed sensitivity and specificity for medical applications.
IEEE Control Systems Letters, vol. 2, issue 3, 393 - 398, 2018.

M.C. Campi, S. Garatti, F.A. Ramponi
A General Scenario Theory for Nonconvex Optimization and Decision making.

IEEE Trans. on Automatic Control, AC-63, 4067-4078, 2018.


M.C. Campi and S. Garatti.
Wait-and-Judge Scenario Optimization.
Mathematical Programming
, 167(1), 155-189, 2018.

F.A. Ramponi, M.C. Campi.
Expected shortfall: Heuristic and certificates.
European Journal of Operational Research, 267, 1003-1013, 2018.
 

E. Weyer, M.C. Campi, B.C. Csaji,
Asymptotic properties of SPS confidence regions.
Automatica, Vol. 82, pp. 287-294, 2017.

H. Ming, L. Xie, M.C. Campi, S. Garatti, P. R. Kumar.

Scenario-based Economic Dispatch with Uncertain Demand Response.
IEEE Trans. on Smart Grid, 2017.
DOI: 10.1109/TSG.2017.2778688.

A. Carč, B.C. Csaji, M.C. Campi and E. Weyer.
Finite-Sample System Identification: An overview and a new correltation method.
IEEE Control Systems Letters, DOI
10.1109/LCSYS.2017.2720969,Online ISSN: 2475-1456 , 2017.

A. Caré, S. Garatti and M.C. Campi.
A Coverage Theory  for Least Squares.
Journal of the Royal Statistical Society B, 79, Part 5, pp. 1367–1389, 2017.

S. Ko, E. Weyer and M.C. Campi,
Non-asymptotic model quality assessment of transfer functions at multiple frequency points.
Automatica,  60:65-78, 2015.

A. Caré, S. Garatti and M.C. Campi.
Scenario min-max optimization and the risk of empirical costs.
SIAM Journal on Optimization, 25, no.4: 2061-2080, 2015.
(article winner of the 2016 stochastic programming student paper prize)

B.C. Csaji, M.C. Campi and E. Weyer.
Sign-Perturbed Sums: A New System Identificaiton Approach for Contructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models.
IEEE Trans. on Signal Processing, 63, no.1: 169-181, 2015.

S. Ko, E. Weyer and   M.C. Campi.
Non-asymptotic model quality assessment of transfer functions at multiple frequency points.
Automatica,  60:65-78, 2015.

A. Caré, S. Garatti and M.C. Campi.
FAST - Fast Algorithm for the Scenario Technique.
Operations Research, 62, no.3: 662-671, 2014.

M.C. Campi and A. Carč.
Random convex programs with L1-regularization: sparsity and generalization.
SIAM Journal on Control and Optimization, 51, no.5: 3532-3557, 2013.

S. Garatti and M.C. Campi.
Modulating Robustness in Control Design: Principles and Algorithms.
IEEE Control Systems Magazine, 33: 36–51, 2013.

B.K. Pagnoncelli, D. Reich and M.C. Campi.
Risk-Return Trade-off with the Scenario Approach in Practice: A Case Study in Portfolio Selection.
J. of Optimization Theory and Applications, 155: 707-722, 2012.

M.C. Campi and S. Garatti.
A Sampling-and-Discarding Approach to Chance-Constrained Optimization:  Feasibility and Optimality.
J. of Optimization Theory and Applications, 148: 257–280, 2011.

M.C. Campi.

Why is resorting to fate wise? A critical look at randomized algorithms in systems and control.

European Journal of Control, 5:419-430, 2010.

M.C. Campi.

discussion on paper: "Why is resorting to fate wise? A critical look at randomized algorithms in systems and control" - Final comments by the author. 

European Journal of Control, 5:440-441, 2010.

M.C. Campi.

Classification with Guaranteed Probability of Error.

Machine Learning, 80:63-84, 2010.

M.C. Campi and E. Weyer.

Non-asymptotic confidence sets for the parameters of linear transfer functions.

IEEE Trans. on Automatic Control, AC-55, 2708-2720, 2010.

S Garatti, S. Bittanti and M.C. Campi.
Iterative robust control: speeding up improvement through iterations.

Syst. Contr. Lett., 59:139-146, 2010.

M.C. Campi, S. Garatti and M. Prandini.
The Scenario Approach for Systems and Control Design.
Annual Reviews in Control, 33:149-157, 2009.

M.C. Campi, S. Ko and E. Weyer.
Non-asymptotic confidence regions for model parameters in the presence of unmodelled dynamics.
Automatica,  45:2175-2186, 2009.

M.C. Campi, G. Calafiore and S. Garatti.
Interval Predictor Models: Identification and Reliability.
Automatica, 45:382-392, 2009.

M.C. Campi and G. Calafiore.
Notes on the scenario design approch.
IEEE Trans. on Automatic Control, AC-54, 382-385, 2009.

M.C. Campi and S. Garatti.
The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs. 
SIAM Journal on Optimization, 19, no.3: 1211-1230, 2008.

M.C. Campi, T. Sugie and F. Sakai
An iterative identification method  for linear continuous-time systems.
IEEE Trans. on Automatic Control, AC-53:1661-1669, 2008.

M. Dalai, E. Weyer and M.C. Campi.
Parameter Identification for Nonlinear Systems: Guaranteed Confidence regions through LSCR.
Automatica, 43:1418-1425, 2007.

S. Bittanti and M.C. Campi.
Adaptive Control of Linear Time Invariant Systems: The ``Bet On the Best" Principle.
Communications in Information and Systems, 6:299-320, 2006.

T. Katayama, T. McKelvey, A. Sano, C. Cassandras and M.C. Campi.
Trends in systems and signals.
Annual Reviews in Control, 30:5-17, 2006.

G. Calafiore and M.C. Campi.
The Scenario Approach to Robust Control Design.
IEEE Trans. on Automatic Control, AC-51:742-753, 2006.

M.C. Campi and S.M. Savaresi.
Direct nonlinear control design: the Virtual Reference Feedback Tuning (VRFT) approach.
IEEE Trans. on Automatic Control, AC-51:14-27, 2006.

S. Garatti, M.C. Campi and S. Bittanti.
The asymptotic model quality assessment for instrumental variable identification revisited.
Syst. Contr. Lett., 55:494-500, 2006.

M.C. Campi and E. Weyer.
Guaranteed non-asymptotic confidence regions in system identification.
Automatica, 41:1751-1764, 2005.
(the downloadable file is an extended version (with all proofs) of the Automatica paper)

G. Calafiore and M.C. Campi.
Uncertain convex programs: randomized solutions and confidence levels.
Mathematical Programming, 102, no.1: 25-46, 2005.
Electronic version made available by SPRINGER at: DOI 10.1007/s10107-003-0499-y

M.C. Campi, Su Ki Ooi and E. Weyer.
Non-asymptotic quality assessment of generalised FIR models with periodic inputs.
Automatica, 40:2029-2041, 2004. 

S. Garatti, M.C. Campi and S. Bittanti.
Assessing the quality of identified models through the asymptotic theory - When is the result reliable?
Automatica, 40:1319-1332, 2004.

M.C. Campi, J.P. Hespanha and M. Prandini.
Cautious hierarchical switching control of stochastic linear systems.
Int. J. Adapt. Control and Signal Process., invited paper for the Special Issue on "New Approaches to Adaptive Control", 18:319-333, 2004.

G. Calafiore and M.C. Campi.
A learning theory approach to the construction of predictor models.
Discrete and Continuous Dynamical Systems (ISSN 1078-0947), 156:166, supplement volume 2003.

M.C. Campi, A. Lecchini and S.M. Savaresi.
An application of the virtual reference feedback tuning method to a benchmark problem.
European Journal of Control, Special Issue on  "Design and Optimisation of Restricted Complexity Controllers", 1:66-76, 2003.

M.C. Campi and M. Prandini.
Randomized algorithms for the synthesis of cautious adaptive controllers.
Syst. Contr. Lett., invited paper for the Special Issue on "Adaptive Systems", 49:21-36, 2003.

A. Lecchini, M.C. Campi and S.M. Savaresi.
Virtual Reference Feedback Tuning for two degree of freedom controllers.
Int. J. Adapt. Control and Signal Process., invited paper for the Special Issue on "New Ideas in Recursive Estimation and stochastic Adaptive Control", 16:355-371, 2002.

M.C. Campi and E. Weyer.
Finite sample properties of system identification methods.
IEEE Trans. on Automatic Control, AC-47:1329-1334, 2002.

E. Weyer and M.C. Campi.
Non-asymptotic confidence ellipsoids for the least squares estimate.
Automatica, 38:1529-1547, 2002.

M. C. Campi, A. Lecchini and S.M. Savaresi.
Virtual Reference Feedback Tuning: a Direct Method for the Design of Feedback Controllers.
Automatica, 38:1337-1346, 2002.

M.C. Campi and M. Vidyasagar.
Learning with prior information.
IEEE Trans. on Automatic Control, AC-46:1682-1695, 2001.

M.Prandini and M.C. Campi.
Adaptive LQG control of input-output systems - A cost-biased approach.
SIAM J. Control and Optim., 39, no 5: 1499-1519, 2001.

S. Bittanti and  M.C. Campi.
Persistence of excitation properties for time-varying autoregressive systems.
SIAM J. Control and Optim., 39, no.1:133-140, 2001.

S. Bittanti, P. Bolzern, M.C. Campi, A. De Marco, G. Poncia and W. Prandoni.
Modelling of a fluidised bed combustors with char mass estimation purposes.
IEEE Trans. on Control Systems technology, CST-8:247--256, 2000.

M.C. Campi and P.R. Kumar.
Adaptive Linear Quadratic Gaussian control: the cost-biased approach revisited.
SIAM J. Control and Optim., 36, no.6:1890-1907, 1998.

M.C. Campi and P.R. Kumar.
Learning dynamical systems in a stationary environment.
Syst. Contr. Lett., Special Issue on "Learning Theory", 34:125-132, 1998.

M. Prandini and M.C. Campi.
A new recursive identification algorithm for singularity free adaptive control.
Syst. Contr. Lett., 34:177-183, 1998.

M. Prandini, S. Bittanti and M.C. Campi.
A penalized identification criterion for securing controllability in adaptive control.
J. of Mathematical Systems, Estimation and Control. Summary in vol.8, no.4: 491-494, retrieval code for full electronic manuscript: 29460, 1998.

M.C. Campi.
A unique representation theorem for the conditional expectation of stationary processes and application to dynamic estimation problems.
J. of Applied Probability, 34:372-380, 1997.

M.C. Campi.
Performance of RLS identification algoritms with forgetting factor: a $\phi$-mixing approach.
J. of Mathematical Systems, Estimation and Control, 7:29-53, 1997.

S. Bittanti, M.C. Campi, and S. Savaresi.
Unbiased estimation of a sinusoid in colored noise via adapted notch filters.
Automatica, 33:209-215, 1997.

M. Prandini, M.C. Campi, and R. Leonardi.
Optimal delay estimation and performance evaluation in blind equalization.
Int. J. Adapt. Control and Signal Process., 11:621-640, 1997.

M.C. Campi and M. James.
Nonlinear discrete-time risk-sensitive optimal control.
Int. J. Robust and Nonlinear Control, 6:1-19, 1996.

M.C. Campi.
The problem of pole-zero cancellation in transfer function identification and application to adaptive stabilization.
Automatica, 32:849-857, 1996.

M.C. Campi.
Adaptive control of non-minimum phase systems.
Int. J. Adapt. Control and Signal Process., 9:137-149, 1995.

M.C. Campi.
Exponentially weighted least squares identification of time-varying systems with white disturbances.
IEEE Trans. on Signal Processing, SP-42:2906-2914, 1994.

M.C. Campi.
Reflections on "adaptive prediction".
J. of the Franklin Institute, 331B:251-264, 1994.

S. Bittanti and M.C. Campi.
Bounded error identification of time-varying parameters by RLS techniques.
IEEE Trans. on Automatic Control, AC-39:1106-1110, 1994.

M.C. Campi, W.S. Lee, and B.D.O. Anderson.
New filters for internal model control design.
Int. J. Robust and Nonlinear Control, 4:757-775, 1994.

S. Bittanti, M.C. Campi and F. Lorito.
Effective identification algorithms for adaptive control.
Int. J. Adapt. Control and Signal Process., 6:221-235, 1992.

S.Bittanti and M.C. Campi.
Some remarks on self-tuning controllers based on least squares and modified least squares: a comprehensive approach.
Technical Cybernetics, 6:48-54, 1992 (in Russian).

M.C. Campi.
On the convergence of minimum-variance directional-forgetting adaptive control schemes.
Automatica, 28:221-225, 1991.

S. Bittanti and M.C. Campi.
Adaptive RLS algorithms under stochastic excitation - $l^2$ convergence analysis.
IEEE Trans. on Automatic Control, AC-36:963-967, 1991.

S. Bittanti and M.C. Campi.
Adaptive RLS algorithms under stochastic excitation - strong consistency analysis.
Syst. Contr. Lett., 17:3-8, 1991.

S. Bittanti, P. Bolzern, and M.C. Campi.
Recursive least squares identification algorithms with incomplete excitation: convergence analysis and application to adaptive control.
IEEE Trans. on Automatic Control, AC-35:1371-1373, 1990.

S. Bittanti, P. Bolzern, and M.C. Campi.
Convergence and exponential convergence of identification algorithms with directional forgetting  factor.
Automatica, 26:929-932, 1990.

S. Bittanti, P. Bolzern, and M.C. Campi.
Exponential convergence of a modified directional forgetting identification algorithm.
Syst. Contr. Lett., 14:131-137, 1990.

S. Bittanti, P. Bolzern, and M.C. Campi.
A counterexample to the exponential convergence of the directional forgetting algorithm.
Int. J. Adapt. Control and Signal Process., 4:237-244, 1990.

S. Bittanti, P. Bolzern, and M.C. Campi.
Adaptive identification via prediction-error directional forgetting factor: convergence analysis.
Int. J. Contr., 50:2407-2421, 1989.