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Articles in Journals
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.
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.
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.
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.
Machine Learning,
80:63-84, 2010.
M.C. Campi and E. Weyer.
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.