G. Pillonetto

发表

Gaussian Processes for Wiener-Hammerstein system identification

G. Pillonetto, A. Chiuso, 2009 .

G. Pillonetto, A. Aravkin, Anna Scampicchio, 2020 .

Robot motion planning using adaptive random walks

Stefano Carpin, Gianluigi Pillonetto, G. Pillonetto, 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

Mathematical foundations of stable RKHSs pdf

Mauro Bisiacco, Gianluigi Pillonetto, G. Pillonetto, 2020, Autom..

Efficient algorithms for large scale linear system identification using stable spline estimators

Francesca P. Carli, G. Pillonetto, A. Chiuso, 2012 .

Subspace identification using predictor estimation via Gaussian regression

Alessandro Chiuso, Giuseppe De Nicolao, Gianluigi Pillonetto, 2008, 2008 47th IEEE Conference on Decision and Control.

Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering pdf

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2017, Autom..

Bayesian and nonparametric methods for system identification and model selection

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2014, 2014 European Control Conference (ECC).

Identification of Time-Varying Systems in Reproducing Kernel Hilbert Spaces

Gianluigi Pillonetto, G. Pillonetto, 2008, IEEE Transactions on Automatic Control.

Estimating parameters and stochastic functions of one variable using nonlinear measurement models

G. Pillonetto, B. Bell, 2004 .

Learning Output Kernels with Block Coordinate Descent

Peter V. Gehler, Cheng Soon Ong, Gianluigi Pillonetto, 2011, ICML.

Robust and Trend-following Kalman Smoothers using Student's t

James V. Burke, Gianluigi Pillonetto, Aleksandr Y. Aravkin, 2010, 1001.3907.

Learning using state space kernel machines

J. Burke, G. Pillonetto, A. Aravkin, 2011 .

Wavelet estimation by Bayesian thresholding and model selection

Eugenio Cinquemani, Gianluigi Pillonetto, G. Pillonetto, 2008, Autom..

Outlier robust kernel-based system identification using ℓ1-Laplace techniques

Giulio Bottegal, Håkan Hjalmarsson, Aleksandr Y. Aravkin, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

On the MSE Properties of Empirical Bayes Methods for Sparse Estimation

J. Burke, G. Pillonetto, A. Chiuso, 2012 .

System identification using kernel-based regularization: New insights on stability and consistency issues

Gianluigi Pillonetto, G. Pillonetto, 2018, Autom..

Generalized System Identification with Stable Spline Kernels

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, SIAM J. Sci. Comput..

An inequality constrained nonlinear Kalman-Bucy smoother by interior point likelihood maximization

James V. Burke, Gianluigi Pillonetto, Bradley M. Bell, 2009, Autom..

Distributed statistical estimation of the number of nodes in sensor networks

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2010, 49th IEEE Conference on Decision and Control (CDC).

Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, 53rd IEEE Conference on Decision and Control.

Distributedparametricandnonparametricregressionwith on-lineperformanceboundscomputation

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

Robust Singular Smoothers for Tracking Using Low-Fidelity Data

Sarah E. Webster, James V. Burke, Gianluigi Pillonetto, 2019, Robotics: Science and Systems.

Approximating the Bayesian inverse for nonlinear dynamical systems

G. Pillonetto, B. Bell, 2008 .

6 – New Trends in Nonparametric Linear System Identification1

G. Pillonetto, G. Nicolao, 2014 .

Identification of Large Scale Systems : the Po River case study

G. Pillonetto, Laureanda Silvia Minucelli, 2012 .

Identificationoflarge-scalesparselineardynamicsystems:a regularizationbasedapproach

G. Pillonetto, A. Chiuso, 2010 .

Nonlinear system identification via Gaussian regression and mixtures of kernels

G. Pillonetto, A. Chiuso, M. H. Quang, 2009 .

Estimating inputs of nonlinear dynamical systems using differential algebra techniques

G. Pillonetto, M. Saccomani, 2005 .

AnInequalityConstrainedNonlinear Kalman-Bucy Smoother byInteriorPointLikelihood Maximization ?

J. Burke, G. Pillonetto, B. Bell, 2008 .

Optimization viewpoint on Kalman smoothing, with applications to robust and sparse estimation

J. Burke, G. Pillonetto, A. Aravkin, 2013, 1303.1993.

A distributed Kalman smoother

G. Pillonetto, B. Bell, 2009 .

Stable andRobustLQRDesign via ScenarioApproach

G. Pillonetto, A. Aravkin, Anna Scampicchio, 2020 .

Dynamic insulin sensitivity index: importance in diabetes.

Claudio Cobelli, Andrea Caumo, Gianluigi Pillonetto, 2010, American journal of physiology. Endocrinology and metabolism.

Minimal model S(I)=0 problem in NIDDM subjects: nonzero Bayesian estimates with credible confidence intervals.

Giovanni Sparacino, Claudio Cobelli, Riccardo Bellazzi, 2002, American journal of physiology. Endocrinology and metabolism.

FastRobustMethods for Singular State-SpaceModels

J. Burke, G. Pillonetto, A. Aravkin, 2018 .

New Stability Results and Algorithms for Block Tridiagonal Systems, with Applications to Kalman Smoothing

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013 .

diabetesinsulin sensitivity index: importance in

G. Pillonetto, C. Cobelli, A. Caumo, 2011 .

New stable spline estimators for robust, sparse and inequality constrained linear system identification

J. Burke, G. Pillonetto, A. Aravkin, 2013 .

Robust andTrend-following Student ’ s t-KalmanSmoothers ?

J. Burke, G. Pillonetto, A. Aravkin, 2011 .

On the Estimation of Hyperparameters for Empirical Bayes Estimators: Maximum Marginal Likelihood vs Minimum MSE

Alessandro Chiuso, Aleksandr Y. Aravkin, James V. Burke, 2012 .

Assessment of clinical data of nonlinear stochastic deconvolution versus block-circulant singular value decomposition for quantitative dynamic susceptibility contrast magnetic resonance imaging.

G. Pillonetto, C. Cobelli, M. Cosottini, 2011, Magnetic resonance imaging.

Estimation of arterial arrival time and cerebral blood flow from QUASAR arterial spin labeling using stable spline

G. Pillonetto, X. Golay, M. Chappell, 2015, Magnetic resonance in medicine.

Sparse dynamical models for thermodynamic identification of buildings

G. Pillonetto, A. Chiuso, A. Beghi, 2011 .

Distributed size estimation in anonymous networks

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

INSULIN SENSITIVITY INDEX ALSO ACCOUNTING FOR INSULIN ACTION DYNAMICS: IMPORTANCE IN DIABETES

G. Pillonetto, C. Cobelli, A. Caumo, 2006 .

Dealing with collinearity in large-scale linear system identification using Bayesian regularization

G. Pillonetto, Wenqi Cao, 2022, 2022 IEEE 61st Conference on Decision and Control (CDC).

A novel Multiplicative Polynomial Kernel for Volterra series identification

G. Pillonetto, R. Carli, A. D. Libera, 2019, IFAC-PapersOnLine.

Stable spline deconvolution for dynamic susceptibility contrast MRI

G. Pillonetto, A. Bertoldo, D. Peruzzo, 2017, Magnetic resonance in medicine.

Bayesian frequentist bounds for machine learning and system identification

G. Pillonetto, Anna Scampicchio, Giacomo Baggio, 2022, Autom..

Sparse estimation in linear dynamic networks using the stable spline horseshoe prior

G. Pillonetto, A. Yazdani, 2022, Autom..

On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses

Tianshi Chen, Gianluigi Pillonetto, Tianshi Chen, 2018, Autom..

Multi-robots Gaussian estimation and coverage control: From client-server to peer-to-peer architectures

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2017, Autom..

Generalized Kalman smoothing: Modeling and algorithms

Lennart Ljung, Aleksandr Y. Aravkin, James V. Burke, 2016, Autom..

The interplay between system identification and machine learning pdf

Gianluigi Pillonetto, G. Pillonetto, 2016, ArXiv.

Robust EM kernel-based methods for linear system identification pdf

Giulio Bottegal, Håkan Hjalmarsson, Aleksandr Y. Aravkin, 2014, Autom..

Identification of stable models via nonparametric prediction error methods

Alessandro Chiuso, Gianluigi Pillonetto, Diego Romeres, 2015, 2015 European Control Conference (ECC).

Bayesian and regularization approaches to multivariable linear system identification: The role of rank penalties

Alessandro Chiuso, Gianluigi Pillonetto, Giulia Prando, 2014, 53rd IEEE Conference on Decision and Control.

Kernel methods in system identification, machine learning and function estimation: A survey

Lennart Ljung, Tianshi Chen, Giuseppe De Nicolao, 2014, Autom..

Regularized spectrum estimation using stable spline kernels

Giulio Bottegal, Gianluigi Pillonetto, G. Pillonetto, 2013, Autom..

Bayesian learning of probability density functions: A Markov chain Monte Carlo approach

Damiano Varagnolo, Simone Del Favero, Gianluigi Pillonetto, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Prediction error identification of linear systems: A nonparametric Gaussian regression approach

Roland Tóth, Gianluigi Pillonetto, Mohamed Abdelmonim Hassan Darwish, 2011, Autom..

Client–Server Multitask Learning From Distributed Datasets

Giuseppe De Nicolao, Gianluigi Pillonetto, Francesco Dinuzzo, 2008, IEEE Transactions on Neural Networks.

Regularized estimation of sums of exponentials in spaces generated by stable spline kernels

Alessandro Chiuso, Giuseppe De Nicolao, Gianluigi Pillonetto, 2010, Proceedings of the 2010 American Control Conference.

A new kernel-based approach for linear system identification

Giuseppe De Nicolao, Gianluigi Pillonetto, G. Pillonetto, 2010, Autom..

Fast computation of smoothing splines subject to equality constraints

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2009, Autom..

Predictor estimation via Gaussian regression

Alessandro Chiuso, Giuseppe De Nicolao, Gianluigi Pillonetto, 2008, 2008 47th IEEE Conference on Decision and Control.

Solutions of nonlinear control and estimation problems in reproducing kernel Hilbert spaces: Existence and numerical determination

Gianluigi Pillonetto, G. Pillonetto, 2008, Autom..

Multirobot localization with unknown variance parameters using iterated Kalman filtering

Stefano Carpin, Gianluigi Pillonetto, G. Pillonetto, 2007, 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Bayes and empirical Bayes semi-blind deconvolution using eigenfunctions of a prior covariance

Gianluigi Pillonetto, Bradley M. Bell, G. Pillonetto, 2007, Autom..

Identifiability of the stochastic semi-blind deconvolution problem for a class of time-invariant linear systems

Claudio Cobelli, Gianluigi Pillonetto, G. Pillonetto, 2007, Autom..

Input estimation in nonlinear dynamical systems using differential algebra techniques

Gianluigi Pillonetto, Maria Pia Saccomani, G. Pillonetto, 2006, Autom..

Handling Non-Negativity in Deconvolution of Physiological Signals: A Nonlinear Stochastic Approach

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2002, Annals of Biomedical Engineering.

Bayesian Deconvolution of Functions in RKHS Using MCMC Techniques

Gianluigi Pillonetto, Bradley M. Bell, G. Pillonetto, 2003, System Modelling and Optimization.

The quest for the right kernel in Bayesian impulse response identification: The use of OBFs

Mohamed Darwish, Roland Tóth, Gianluigi Pillonetto, 2018, Autom..

Bayesian identification of LPV Box-Jenkins models

Mohamed Darwish, Roland Tóth, Gianluigi Pillonetto, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

Consistent identification of Wiener systems: A machine learning viewpoint

Gianluigi Pillonetto, G. Pillonetto, 2013, Autom..

Newton-Raphson Consensus for Distributed Convex Optimization

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2015, IEEE Transactions on Automatic Control.

The convergence rate of Newton-Raphson consensus optimization for quadratic cost functions

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Multidimensional Newton-Raphson consensus for distributed convex optimization

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2012, 2012 American Control Conference (ACC).

Newton-Raphson consensus for distributed convex optimization

G. Pillonetto, D. Varagnolo, L. Schenato, 2011, IEEE Conference on Decision and Control and European Control Conference.

A convex approach to robust LQR

Gianluigi Pillonetto, Anna Scampicchio, G. Pillonetto, 2020, 2020 59th IEEE Conference on Decision and Control (CDC).

Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint pdf

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2015, Autom..

A new kernel-based approach to hybrid system identification

Gianluigi Pillonetto, G. Pillonetto, 2016, Autom..

The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, J. Mach. Learn. Res..

Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2010, NIPS.

A new kernel-based approach for system identification

Giuseppe De Nicolao, Gianluigi Pillonetto, G. Pillonetto, 2008, 2008 American Control Conference.

Distributed Kalman smoothing in static Bayesian networks

Simone Del Favero, Gianluigi Pillonetto, Bradley M. Bell, 2013, Autom..

Nonsmooth regression and state estimation using piecewise quadratic log-concave densities

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

A new kernel-based approach to system identification with quantized output data pdf

Giulio Bottegal, Håkan Hjalmarsson, Gianluigi Pillonetto, 2016, Autom..

Stable and robust LQR design via scenario approach

Gianluigi Pillonetto, Anna Scampicchio, Aleksandr Aravkin, 2020, Autom..

Stable spline identification of linear systems under missing data pdf

Alessandro Chiuso, Giuseppe De Nicolao, Gianluigi Pillonetto, 2019, Autom..

A variation of the Newton-Pepys problem and its connections to size-estimation problems

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2013 .

Distributed parametric and nonparametric regression with on-line performance bounds computation

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2012, Autom..

Deep networks for system identification: a Survey

Antônio H. Ribeiro, L. Ljung, G. Pillonetto, 2023, ArXiv.

Bayesian kernel-based system identification with quantized output data pdf

Giulio Bottegal, Håkan Hjalmarsson, Gianluigi Pillonetto, 2015, ArXiv.

Tuning complexity in regularized kernel-based regression and linear system identification: The robustness of the marginal likelihood estimator

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2015, Autom..

Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets

Alessandro Chiuso, Gianluigi Pillonetto, Giulia Prando, 2015, 2016 European Control Conference (ECC).

Algorithms for Block Tridiagonal Systems: Stability Results for Generalized Kalman Smoothing

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2021, IFAC-PapersOnLine.

Kalman smoothing with persistent nuisance parameters

Karthikeyan Natesan Ramamurthy, Aleksandr Y. Aravkin, Gianluigi Pillonetto, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Kalman smoothing and block tridiagonal systems: new connections and numerical stability results

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, 1303.5237.

COVID-19 epidemic control using short-term lockdowns for collective gain

Mauro Bisiacco, Gianluigi Pillonetto, G. Pillonetto, 2021, Annual Reviews in Control.

Tracking the time course of reproduction number and lockdown’s effect on human behaviour during SARS-CoV-2 epidemic: nonparametric estimation

G. Pillonetto, C. Cobelli, M. Bisiacco, 2021, Scientific Reports.

Tracking the time course of reproduction number and lockdown's effect during SARS-CoV-2 epidemic: nonparametric estimation pdf

Mauro Bisiacco, Gianluigi Pillonetto, Claudio Cobelli, 2020, ArXiv.

Distributed Multi-Agent Gaussian Regression via Finite-Dimensional Approximations

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Nonlinear Hybrid Systems Identification using Kernel-Based Techniques

Gianluigi Pillonetto, Anna Scampicchio, Alberto Giaretta, 2018 .

Outlier robust system identification: a Bayesian kernel-based approach

Giulio Bottegal, Aleksandr Y. Aravkin, Gianluigi Pillonetto, 2013, 1312.6317.

Bayesian Online Multitask Learning of Gaussian Processes

Giuseppe De Nicolao, Gianluigi Pillonetto, Francesco Dinuzzo, 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, IEEE Transactions on Automatic Control.

System Identification: A Machine Learning Perspective

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2019, Annu. Rev. Control. Robotics Auton. Syst..

Machine learning meets Kalman Filtering

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Robust and Trend-Following Student's t Kalman Smoothers

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, SIAM J. Control. Optim..

Absolute integrability of Mercer kernels is only sufficient for RKHS stability

G. Pillonetto, M. Bisiacco, 2023, ArXiv.

On the stability test for reproducing kernel Hilbert spaces

G. Pillonetto, M. Bisiacco, 2023, ArXiv.

Dealing with Collinearity in Large-Scale Linear System Identification Using Gaussian Regression

G. Pillonetto, Wenqi Cao, 2023, ArXiv.

Estimation of sparse linear dynamic networks using the stable spline horseshoe prior pdf

Gianluigi Pillonetto, G. Pillonetto, 2021, ArXiv.

Bayesian Kernel-Based Linear Control Design

Simone Formentin, Alessandro Chiuso, Gianluigi Pillonetto, 2019, 2019 IEEE 58th Conference on Decision and Control (CDC).

Kernel absolute summability is only sufficient for RKHS stability pdf

Mauro Bisiacco, Gianluigi Pillonetto, G. Pillonetto, 2019, ArXiv.

On-line Bayesian system identification

Alessandro Chiuso, Gianluigi Pillonetto, Giulia Prando, 2016, 2016 European Control Conference (ECC).

Maximum Entropy vector kernels for MIMO system identification

Alessandro Chiuso, Gianluigi Pillonetto, Giulia Prando, 2015, Autom..

Kernel-based model order selection for identification and prediction of linear dynamic systems

Lennart Ljung, Tianshi Chen, Gianluigi Pillonetto, 2013, 52nd IEEE Conference on Decision and Control.

A Bayesian approach to sparse dynamic network identification

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2012, Autom..

Convex vs nonconvex approaches for sparse estimation: GLasso, Multiple Kernel Learning and Hyperparameter GLasso

Alessandro Chiuso, Aleksandr Y. Aravkin, James V. Burke, 2013, 1302.6434.

Nonparametric sparse estimators for identification of large scale linear systems

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2010, 49th IEEE Conference on Decision and Control (CDC).

Distributed Cardinality Estimation in Anonymous Networks

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2014, IEEE Transactions on Automatic Control.

Consensus based estimation of anonymous networks size using Bernoulli trials

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2012, 2012 American Control Conference (ACC).

Merging the adaptive random walks planner with the randomized potential field planner

Stefano Carpin, Gianluigi Pillonetto, G. Pillonetto, 2005, Proceedings of the Fifth International Workshop on Robot Motion and Control, 2005. RoMoCo '05..

Continuous-time DC kernel — A stable generalized first order spline kernel

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2016, 2016 IEEE 55th Conference on Decision and Control (CDC).

Kernel selection in linear system identification Part I: A Gaussian process perspective

Giuseppe De Nicolao, Gianluigi Pillonetto, G. Pillonetto, 2011, IEEE Conference on Decision and Control and European Control Conference.

Online estimation of variance parameters: Experimental results with applications to localization

Stefano Carpin, Gianluigi Pillonetto, Gorkem Erinc, 2008, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Numerical non-identifiability regions of the minimal model of glucose kinetics: superiority of Bayesian estimation.

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2003, Mathematical biosciences.

WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2002, Comput. Methods Programs Biomed..

A multi-task learning approach for the extraction of single-trial evoked potentials

Giuseppe De Nicolao, Giovanni Sparacino, Gianluigi Pillonetto, 2013, Comput. Methods Programs Biomed..

Fast algorithms for nonparametric population modeling of large data sets

Giuseppe De Nicolao, Claudio Cobelli, Gianluigi Pillonetto, 2009, Autom..

Regularized System Identification

L. Ljung, Tianshi Chen, G. Pillonetto, 2022, Communications and Control Engineering.

Finite-Sample Guarantees for State-Space System Identification Under Full State Measurements

G. Pillonetto, Giacomo Baggio, A. Carè, 2022, 2022 IEEE 61st Conference on Decision and Control (CDC).

Sample Complexity and Minimax Properties of Exponentially Stable Regularized Estimators

Gianluigi Pillonetto, Anna Scampicchio, G. Pillonetto, 2022, IEEE Transactions on Automatic Control.

Full Bayesian identification of linear dynamic systems using stable kernels.

L. Ljung, G. Pillonetto, 2023, Proceedings of the National Academy of Sciences of the United States of America.

Motion planning using adaptive random walks

Stefano Carpin, Gianluigi Pillonetto, G. Pillonetto, 2005, IEEE Transactions on Robotics.

Spectral analysis of the DC kernel for regularized system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

An $\ell _{1}$-Laplace Robust Kalman Smoother

G. Pillonetto, B. M. Bell, A. Y. Aravkin, 2011, IEEE Transactions on Automatic Control.

Kernel Absolute Summability Is Sufficient but Not Necessary for RKHS Stability

Mauro Bisiacco, Gianluigi Pillonetto, G. Pillonetto, 2020, SIAM J. Control. Optim..

Sliding-mode theory under feedback constraints and the problem of epidemic control pdf

Mauro Bisiacco, Gianluigi Pillonetto, G. Pillonetto, 2021, SIAM J. Appl. Math..

Bayesian strategies for calibrating heteroskedastic static sensors with unknown model structures

Damiano Varagnolo, Thomas Gustafsson, Simone Del Favero, 2018, 2018 European Control Conference (ECC).

Sensing, Compression, and Recovery for WSNs: Sparse Signal Modeling and Monitoring Framework

Michele Zorzi, Michele Rossi, Giorgio Quer, 2012, IEEE Transactions on Wireless Communications.

Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method

Giovanni Sparacino, Claudio Cobelli, Gianluigi Pillonetto, 2001, IEEE Transactions on Biomedical Engineering.

Kernel-based methods for Volterra series identification

Ruggero Carli, Gianluigi Pillonetto, Alberto Dalla Libera, 2021, Autom..

Model-Free Radio Map Estimation in Massive MIMO Systems via Semi-Parametric Gaussian Regression

G. Pillonetto, L. Schenato, M. Rossi, 2022, IEEE Wireless Communications Letters.

Optimal smoothing of non-linear dynamic systems via Monte Carlo Markov chains

Gianluigi Pillonetto, Bradley M. Bell, G. Pillonetto, 2008, Autom..

Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso

Alessandro Chiuso, Aleksandr Y. Aravkin, James V. Burke, 2014, J. Mach. Learn. Res..

Kernel methods and Gaussian processes for system identiﬁcation and control

G. Pillonetto, R. Carli, Diego Romeres, 2023 .

A new dynamic index of insulin sensitivity

Giovanni Sparacino, Claudio Cobelli, Andrea Caumo, 2006, IEEE Transactions on Biomedical Engineering.

Linear system identification using the sequential stabilizing spline algorithm

G. Pillonetto, A. Chiuso, 2022, Autom..

Identification of stable linear systems via the sequential stabilizing spline algorithm

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2018 .

The unconstrained and inequality constrained moving horizon approach to robot localization

Stefano Carpin, Aleksandr Y. Aravkin, Gianluigi Pillonetto, 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.

Linear system identification using stable spline kernels and PLQ penalties

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2013, 52nd IEEE Conference on Decision and Control.

A statistical and computational theory for robust and sparse Kalman smoothing

Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, 2011, 1111.2730.

Distributed convex optimization: a consensus-based Newton-Raphson approach

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

An index of parameter reproducibility accounting for estimation uncertainty: theory and case study on β-cell responsivity and insulin sensitivity.

G. Pillonetto, C. Cobelli, C. Dalla Man, 2015, American journal of physiology. Endocrinology and metabolism.

Boosting as a kernel-based method

G. Pillonetto, A. Aravkin, Giulio Bottegal, 2016, Machine Learning.

The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS

J. Burke, G. Pillonetto, A. Aravkin, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Kernel Methods and Gaussian Processes for System Identification and Control: A Road Map on Regularized Kernel-Based Learning for Control

G. Pillonetto, R. Carli, Diego Romeres, 2023, IEEE Control Systems.

Kernel-based learning of orthogonal functions

G. Pillonetto, Anna Scampicchio, M. Bisiacco, 2023, Neurocomputing.

Kernel-based function learning in dynamic and non stationary environments

G. Pillonetto, M. Bisiacco, Alberto Giaretta, 2023, ArXiv.

Bayesian online multi-task learning using regularization networks

Giuseppe De Nicolao, Gianluigi Pillonetto, Francesco Dinuzzo, 2008, 2008 American Control Conference.

Perspectives of orthonormal basis functions based kernels in Bayesian system identification?

Mohamed Darwish, Roland Tóth, Gianluigi Pillonetto, 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

A stable spline convex approach to hybrid systems identification

Aleksandr Y. Aravkin, Gianluigi Pillonetto, G. Pillonetto, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

A New Kernel-Based Approach for NonlinearSystem Identification

Alessandro Chiuso, Gianluigi Pillonetto, Ha Quang Minh, 2011, IEEE Transactions on Automatic Control.

Prediction error identification of linear systems: A nonparametric Gaussian regression approach

Alessandro Chiuso, Giuseppe De Nicolao, Gianluigi Pillonetto, 2011, Autom..

A New Model Selection Approach to Hybrid Kernel-Based Estimation

Gianluigi Pillonetto, Anna Scampicchio, G. Pillonetto, 2018, 2018 IEEE Conference on Decision and Control (CDC).

Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models

Giovanni Sparacino, Andrea Facchinetti, Giada Acciaroli, 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Fast robust methods for singular state-space models

Sarah E. Webster, Aleksandr Y. Aravkin, James V. Burke, 2018, Autom..

Maximum entropy properties of discrete-time first-order stable spline kernel

Lennart Ljung, Francesca P. Carli, Tianshi Chen, 2014, Autom..

A new kernel-based approach for identification of time-varying linear systems

Aleksandr Y. Aravkin, Gianluigi Pillonetto, G. Pillonetto, 2014, 2014 IEEE International Workshop on Machine Learning for Signal Processing (MLSP).

Tuning complexity in kernel-based linear system identification: The robustness of the marginal likelihood estimator

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2014, 2014 European Control Conference (ECC).

Regularization strategies for nonparametric system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2013, 52nd IEEE Conference on Decision and Control.

Sparse multiple kernels for impulse response estimation with majorization minimization algorithms

Lennart Ljung, Francesca P. Carli, Tianshi Chen, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels

Lennart Ljung, Tianshi Chen, Ruggero Carli, 2012, 2012 IEEE 51st IEEE Conference on Decision and Control (CDC).

Regularized spectrum estimation in spaces induced by stable spline kernels

Giulio Bottegal, Gianluigi Pillonetto, G. Pillonetto, 2012, 2012 American Control Conference (ACC).

A Bayesian learning approach to linear system identification with missing data

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

Predictive power of indices derived from models of biological dynamic systems

C. Cobelli, G. Pillonetto, G. Pillonetto, 2008, 2008 American Control Conference.

Online Estimation of Covariance Parameters using Extended Kalman Filtering and Application to Robot Localization

Stefano Carpin, Gianluigi Pillonetto, Gorkem Erinc, 2012, Adv. Robotics.

Efficient Nonparametric Population Modeling for Large Data Sets

Giuseppe De Nicolao, Claudio Cobelli, Gianluigi Pillonetto, 2007, 2007 American Control Conference.

Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso

J. Burke, G. Pillonetto, A. Chiuso, 2011, IEEE Conference on Decision and Control and European Control Conference.

The generalized cross validation filter pdf

Giulio Bottegal, Gianluigi Pillonetto, G. Pillonetto, 2017, Autom..

A multi-task learning approach for the extraction of single-trial evoked potentials

G. Pillonetto, G. Nicolao, A. Goljahani, 2013, Comput. Methods Programs Biomed..

The role of rank penalties in linear system identification

Alessandro Chiuso, Gianluigi Pillonetto, G. Pillonetto, 2015 .

Gene signatures derived from transcriptomic-causal networks stratified colorectal cancer patients for effective targeted therapy

G. Pillonetto, C. Perou, M. Ratain, 2023, Research square.

Gene expression biomarkers differentiate overall survival of colorectal cancer upon targeted therapies

G. Pillonetto, S. Kopetz, A. Yazdani, 2024, Research square.

On the design of multiple kernels for nonparametric linear system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2014, 53rd IEEE Conference on Decision and Control.

Rank-1 kernels for regularized system identification

Lennart Ljung, Tianshi Chen, Alessandro Chiuso, 2013, 52nd IEEE Conference on Decision and Control.