Gianluigi Pillonetto

发表

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..

Bayesian online multi-task learning using regularization networks

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

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

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

Subspace identification using predictor estimation via Gaussian regression

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

Motion planning using adaptive random walks

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

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..

A New Kernel-Based Approach for NonlinearSystem Identification

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

Distributed Kalman filtering for Time-Space Gaussian Processes * *This work is supported by Progetto di Ateneo CPDA147754/14-New statistical learning approach for multi-agents adaptive estimation and coverage control

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2017 .

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).

Bayesian Kernel-Based Linear Control Design

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

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).

Boosting as a kernel-based method

Giulio Bottegal, Aleksandr Y. Aravkin, Gianluigi Pillonetto, 2019, Machine Learning.

Robust Singular Smoothers for Tracking Using Low-Fidelity Data

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

Regularization strategies for nonparametric system identification

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

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.

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.

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).

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..

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).

Auto-tuning procedures for distributed nonparametric regression algorithms

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2015, 2015 European Control Conference (ECC).

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

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

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.

Identification of stable models via nonparametric prediction error methods

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

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

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

Fast robust methods for singular state-space models

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

Predictor estimation via Gaussian regression

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

The interplay between system identification and machine learning pdf

Gianluigi Pillonetto, G. Pillonetto, 2016, ArXiv.

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

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

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.

Bayesian kernel-based system identification with quantized output data pdf

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

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).

Distributed Multi-Agent Gaussian Regression via Finite-Dimensional Approximations

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

Identification of Time-Varying Systems in Reproducing Kernel Hilbert Spaces

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

Distributed consensus-based Bayesian estimation: sufficient conditions for performance characterization

Damiano Varagnolo, Gianluigi Pillonetto, Luca Schenato, 2010, Proceedings of the 2010 American Control Conference.

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).

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

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

Bayesian Online Multitask Learning of Gaussian Processes

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

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.

Generalized Kalman smoothing: Modeling and algorithms

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

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.

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).

Multi-agents adaptive estimation and coverage control using Gaussian regression

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2015, 2015 European Control Conference (ECC).

Bayesian Deconvolution of Functions in RKHS Using MCMC Techniques

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

Bayesian identification of LPV Box-Jenkins models

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

Identification of hybrid systems using stable spline kernels

Gianluigi Pillonetto, 2015, 2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP).

Stable and robust LQR design via scenario approach

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

Distributed Kalman smoothing in static Bayesian networks

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

Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering pdf

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

Kernel-Based Model Order Selection for Linear System Identification

Lennart Ljung, Tianshi Chen, Gianluigi Pillonetto, 2013, ALCOSP.

On the discardability of data in support vector classification problems

Damiano Varagnolo, Simone Del Favero, Luca Schenato, 2011, IEEE Conference on Decision and Control and European Control Conference.

Distributed function and time delay estimation using nonparametric techniques

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2009, Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference.

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).

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

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

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

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

A novel Multiplicative Polynomial Kernel for Volterra series identification pdf

Ruggero Carli, Gianluigi Pillonetto, Alberto Dalla Libera, 2019, ArXiv.

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.

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.

Outlier robust system identification: a Bayesian kernel-based approach

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

A novel nonparametric approach for the identification of the glucose-insulin system in Type 1 diabetic patients

Giuseppe De Nicolao, Claudio Cobelli, Simone Del Favero, 2011 .

RobustandTrend-following Student'st-KalmanSmoothers ?

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

Kernel absolute summability is only sufficient for RKHS stability pdf

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

Consistent identification of Wiener systems: A machine learning viewpoint

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

Identification of stable linear systems via the sequential stabilizing spline algorithm

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

A convex approach to robust LQR

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

Regularized spectrum estimation using stable spline kernels

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

Bayesian identification of LPV-BJ models : a multidimensional kernel approach

Gianluigi Pillonetto, Roland Toth, Mah Mohamed Darwish, 2015 .

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

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

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

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

A new kernel-based approach for system identification

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

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.

A new kernel-based approach to hybrid system identification

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

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.

Generalized System Identification with Stable Spline Kernels

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

A Bayesian approach to sparse dynamic network identification

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

Robust and Trend-Following Student's t Kalman Smoothers

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

Statistical bounds for Gaussian regression algorithms based on Karhunen-Loève expansions

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2017, 2017 IEEE 56th Annual Conference on Decision and Control (CDC).

A statistical and computational theory for robust and sparse Kalman smoothing

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

Machine learning meets Kalman Filtering

Ruggero Carli, Luca Schenato, Gianluigi Pillonetto, 2016, 2016 IEEE 55th 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).

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).

Learning Output Kernels with Block Coordinate Descent

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

Stable spline identification of linear systems under missing data pdf

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

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..

A new dynamic index of insulin sensitivity

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

System Identification: A Machine Learning Perspective

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

Kernel-based SPS

Gianluigi Pillonetto, Marco C. Campi, Algo Carè, 2018 .

A new kernel-based approach for linear system identification

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

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

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

A kernel-based approach for quantification of dynamic PET studies

Gaia Rizzo, Gianluigi Pillonetto, Denis Peruzzo, 2013 .

UNCERTAINTY BOUNDS FOR KERNEL-BASED REGRESSION: A BAYESIAN SPS APPROACH

Gianluigi Pillonetto, Marco C. Campi, Algo Carè, 2018, 2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP).

Asynchronous Newton-Raphson Consensus for Distributed Convex Optimization

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2012 .

The generalized cross validation filter pdf

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

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

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

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).

Proprioceptive Robot Collision Detection through Gaussian Process Regression

Ruggero Carli, Stefano Ghidoni, Gianluigi Pillonetto, 2019, 2019 American Control Conference (ACC).

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..

Nonlinear Stochastic Regularization to Characterize Tissue Residue Function in Bolus-Tracking MRI: Assessment and Comparison With SVD, Block-Circulant SVD, and Tikhonov

Alessandra Bertoldo, Claudio Cobelli, Gianluigi Pillonetto, 2009, IEEE Transactions on Biomedical Engineering.

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.

Bayesian and nonparametric methods for system identification and model selection

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

Wavelet estimation by Bayesian thresholding and model selection

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

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).

Distributed Cardinality Estimation in Anonymous Networks

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

Mathematical foundations of stable RKHSs pdf

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

Nonlinear Hybrid Systems Identification using Kernel-Based Techniques

Gianluigi Pillonetto, Anna Scampicchio, Alberto Giaretta, 2018 .

Distributedparametricandnonparametricregressionwith on-lineperformanceboundscomputation

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

Client–Server Multitask Learning From Distributed Datasets

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

Multidimensional Newton-Raphson consensus for distributed convex optimization

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

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).

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).

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

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

Efficient Nonparametric Population Modeling for Large Data Sets

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

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).

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).

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).

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

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

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.

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

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

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.

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.

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).

Fast algorithms for nonparametric population modeling of large data sets

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

Distributed multi-agent Gaussian regression via Karhunen-Loève expansions pdf

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2017, ArXiv.

Finding Potential Support Vectors in Separable Classification Problems

Damiano Varagnolo, Simone Del Favero, Luca Schenato, 2013, IEEE Transactions on Neural Networks and Learning Systems.

Regularized spectrum estimation in spaces induced by stable spline kernels

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

The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields pdf

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

Robust EM kernel-based methods for linear system identification pdf

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

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.

STODEC (STOchastic DEConvolution): A Program for Input Estimation in Physiological and Pharmacokinetic Systems

Giuseppe De Nicolao, Giovanni Sparacino, Claudio Cobelli, 2000 .

Pitfalls of the parametric approaches exploiting cross-validation for model order selection*

Giuseppe De Nicolao, Gianluigi Pillonetto, 2012 .

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

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

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

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

Kernel Absolute Summability Is Sufficient but Not Necessary for RKHS Stability

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

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

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

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.

Input estimation in nonlinear dynamical systems using differential algebra techniques

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

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

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

On-line Bayesian system identification

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

Consensus based estimation of anonymous networks size using Bernoulli trials

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

Rank-1 kernels for regularized system identification

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

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

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

Fast computation of smoothing splines subject to equality constraints

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

Newton-Raphson Consensus for Distributed Convex Optimization

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

Maximum Entropy vector kernels for MIMO system identification

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

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).

Deep prediction networks

Gianluigi Pillonetto, Alberto Dalla Libera, 2022, Neurocomputing.

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

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

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

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

Kernel-based methods for Volterra series identification

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

Sample Complexity and Minimax Properties of Exponentially Stable Regularized Estimators

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

Linear Model Identification for Personalized Prediction and Control in Diabetes

Giovanni Sparacino, Andrea Facchinetti, Simone Del Favero, 2022, IEEE Trans. Biomed. Eng..

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

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

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

Gianluigi Pillonetto, G. Pillonetto, 2021, ArXiv.

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

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

The role of rank penalties in linear system identification

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

Deconvolution of non-stationary physical signals: a?smooth variance model for insulin secretion rate

Gianluigi Pillonetto, Bradley M. Bell, 2004 .

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

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

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

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

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

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

Sensing , Compression and Recovery for Wireless Sensor Networks : Sparse Signal Modelling

Michele Zorzi, Michele Rossi, Giorgio Quer, 2011 .

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

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2013 .

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

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

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.

Distributed size estimation in anonymous networks

Damiano Varagnolo, Luca Schenato, Gianluigi Pillonetto, 2011 .

Reconstruction of non-stationary biological signals via stochastic deconvolution

Giovanni Sparacino, Gianluigi Pillonetto, 2000 .