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Gianluigi Pillonetto
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2020 – today
- 2025
- [j80]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Daniel Gedon, Lennart Ljung, Antônio H. Ribeiro, Thomas B. Schön:
Deep networks for system identification: A survey. Autom. 171: 111907 (2025) - 2024
- [j79]Gianluigi Pillonetto, Mauro Bisiacco:
Kernel-based linear system identification: When does the representer theorem hold? Autom. 159: 111347 (2024) - [j78]Mauro Bisiacco, Gianluigi Pillonetto:
A refinement of the stability test for reproducing kernel Hilbert spaces. Autom. 163: 111606 (2024) - [j77]Wenqi Cao, Gianluigi Pillonetto:
Dealing with collinearity in large-scale linear system identification using Gaussian regression. Autom. 166: 111708 (2024) - [j76]Mauro Bisiacco, Gianluigi Pillonetto:
Mercer kernel absolute integrability is only sufficient for RKHS stability. Syst. Control. Lett. 191: 105885 (2024) - [j75]Mauro Bisiacco
, Gianluigi Pillonetto
Learning for Control: $\mathcal {L}_{1}$-Error Bounds for Kernel-Based Regression. IEEE Trans. Autom. Control. 69(10): 6530-6545 (2024) - [i32]Riccardo Alessandro Grimaldi, Giacomo Baggio, Ruggero Carli, Gianluigi Pillonetto:
The Bayesian Separation Principle for Data-driven Control. CoRR abs/2409.16717 (2024) - [i31]Mauro Bisiacco, Gianluigi Pillonetto:
Gaussian kernel expansion with basis functions uniformly bounded in ℒ∞. CoRR abs/2410.01394 (2024) - 2023
- [j74]Anna Scampicchio, Mauro Bisiacco, Gianluigi Pillonetto:
Kernel-based learning of orthogonal functions. Neurocomputing 545: 126237 (2023) - [j73]Mauro Bisiacco, Gianluigi Pillonetto
Sliding-Mode Theory Under Feedback Constraints and the Problem of Epidemic Control. SIAM J. Appl. Math. 83(6): 2189-2211 (2023) - [i30]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Daniel Gedon, Lennart Ljung, Antônio H. Ribeiro, Thomas B. Schön:
Deep networks for system identification: a Survey. CoRR abs/2301.12832 (2023) - [i29]Wenqi Cao, Gianluigi Pillonetto:
Dealing with Collinearity in Large-Scale Linear System Identification Using Gaussian Regression. CoRR abs/2302.10959 (2023) - [i28]Mauro Bisiacco, Gianluigi Pillonetto:
Absolute integrability of Mercer kernels is only sufficient for RKHS stability. CoRR abs/2305.01411 (2023) - [i27]Mauro Bisiacco, Gianluigi Pillonetto:
On the stability test for reproducing kernel Hilbert spaces. CoRR abs/2305.02213 (2023) - [i26]Alberto Giaretta, Mauro Bisiacco, Gianluigi Pillonetto:
Kernel-based function learning in dynamic and non stationary environments. CoRR abs/2310.02767 (2023) - 2022
- [j72]Gianluigi Pillonetto, Alessandro Chiuso
Linear system identification using the sequential stabilizing spline algorithm. Autom. 138: 110169 (2022) - [j71]Mauro Bisiacco, Gianluigi Pillonetto, Claudio Cobelli:
Closed-form expressions and nonparametric estimation of COVID-19 infection rate. Autom. 140: 110265 (2022) - [j70]Giacomo Baggio, Algo Carè, Anna Scampicchio, Gianluigi Pillonetto:
Bayesian frequentist bounds for machine learning and system identification. Autom. 146: 110599 (2022) - [j69]Gianluigi Pillonetto, Akram Yazdani:
Sparse estimation in linear dynamic networks using the stable spline horseshoe prior. Autom. 146: 110666 (2022) - [j68]Alberto Dalla Libera
Deep prediction networks. Neurocomputing 469: 321-329 (2022) - [j67]Gianluigi Pillonetto
Sample Complexity and Minimax Properties of Exponentially Stable Regularized Estimators. IEEE Trans. Autom. Control. 67(5): 2330-2342 (2022) - [j66]Simone Faccioli
Linear Model Identification for Personalized Prediction and Control in Diabetes. IEEE Trans. Biomed. Eng. 69(2): 558-568 (2022) - [j65]Nicolò Dal Fabbro
Model-Free Radio Map Estimation in Massive MIMO Systems via Semi-Parametric Gaussian Regression. IEEE Wirel. Commun. Lett. 11(3): 473-477 (2022) - [c69]Wenqi Cao, Gianluigi Pillonetto:
Dealing with collinearity in large-scale linear system identification using Bayesian regularization. CDC 2022: 196-202 - [c68]Giacomo Baggio, Algo Carè, Gianluigi Pillonetto:
Finite-Sample Guarantees for State-Space System Identification Under Full State Measurements. CDC 2022: 2789-2794 - [i25]Wenqi Cao, Gianluigi Pillonetto:
Dealing with collinearity in large-scale linear system identification using Bayesian regularization. CoRR abs/2203.13633 (2022) - 2021
- [j64]Mauro Bisiacco, Gianluigi Pillonetto:
COVID-19 epidemic control using short-term lockdowns for collective gain. Annu. Rev. Control. 52: 573-586 (2021) - [j63]Anna Scampicchio, Aleksandr Y. Aravkin, Gianluigi Pillonetto:
Stable and robust LQR design via scenario approach. Autom. 129: 109571 (2021) - [j62]Alberto Dalla Libera
Kernel-based methods for Volterra series identification. Autom. 129: 109686 (2021) - [i24]Gianluigi Pillonetto:
Estimation of sparse linear dynamic networks using the stable spline horseshoe prior. CoRR abs/2107.11155 (2021) - [i23]Mauro Bisiacco, Gianluigi Pillonetto:
COVID-19 epidemic control using short-term lockdowns for collective gain. CoRR abs/2109.00995 (2021) - [i22]Mauro Bisiacco, Gianluigi Pillonetto:
Sliding-mode theory under feedback constraints and the problem of epidemic control. CoRR abs/2109.05464 (2021) - 2020
- [j61]Marco Todescato
Efficient spatio-temporal Gaussian regression via Kalman filtering. Autom. 118: 109032 (2020) - [j60]Mauro Bisiacco, Gianluigi Pillonetto:
On the mathematical foundations of stable RKHSs. Autom. 118: 109038 (2020) - [j59]Mauro Bisiacco, Gianluigi Pillonetto:
Kernel Absolute Summability Is Sufficient but Not Necessary for RKHS Stability. SIAM J. Control. Optim. 58(4): 2006-2022 (2020) - [c67]Anna Scampicchio, Gianluigi Pillonetto:
A convex approach to robust LQR. CDC 2020: 3705-3710 - [i21]Mauro Bisiacco, Gianluigi Pillonetto:
Mathematical foundations of stable RKHSs. CoRR abs/2005.02971 (2020) - [i20]Gianluigi Pillonetto, Mauro Bisiacco, Giorgio Palù, Claudio Cobelli:
Tracking the time course of reproduction number and lockdown's effect during SARS-CoV-2 epidemic: nonparametric estimation. CoRR abs/2008.12337 (2020)
2010 – 2019
- 2019
- [j58]Alessandro Chiuso
System Identification: A Machine Learning Perspective. Annu. Rev. Control. Robotics Auton. Syst. 2: 281-304 (2019) - [j57]Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster:
Fast robust methods for singular state-space models. Autom. 105: 399-405 (2019) - [j56]Gianluigi Pillonetto, Alessandro Chiuso
Stable spline identification of linear systems under missing data. Autom. 108 (2019) - [j55]Aleksandr Y. Aravkin
Boosting as a kernel-based method. Mach. Learn. 108(11): 1951-1974 (2019) - [j54]Gianluigi Pillonetto
Distributed Multi-Agent Gaussian Regression via Finite-Dimensional Approximations. IEEE Trans. Pattern Anal. Mach. Intell. 41(9): 2098-2111 (2019) - [c66]Alberto Dalla Libera
Proprioceptive Robot Collision Detection through Gaussian Process Regression. ACC 2019: 19-24 - [c65]Anna Scampicchio, Alessandro Chiuso
Bayesian Kernel-Based Linear Control Design. CDC 2019: 822-827 - [c64]Jonathan Jonker, Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto, Sarah E. Webster:
Robust Singular Smoothers for Tracking Using Low-Fidelity Data. Robotics: Science and Systems 2019 - [i19]Alberto Dalla Libera, Ruggero Carli, Gianluigi Pillonetto:
A novel Multiplicative Polynomial Kernel for Volterra series identification. CoRR abs/1905.07960 (2019) - [i18]Alberto Dalla Libera, Elisa Tosello, Gianluigi Pillonetto, Stefano Ghidoni, Ruggero Carli:
Proprioceptive Robot Collision Detection through Gaussian Process Regression. CoRR abs/1905.08689 (2019) - [i17]Gianluigi Pillonetto, Alessandro Chiuso, Giuseppe De Nicolao:
Stable spline identification of linear systems under missing data. CoRR abs/1908.03913 (2019) - [i16]Mauro Bisiacco, Gianluigi Pillonetto:
Kernel absolute summability is only sufficient for RKHS stability. CoRR abs/1909.02341 (2019) - 2018
- [j53]Mohamed Abdelmonim Hassan Darwish, Gianluigi Pillonetto, Roland Tóth:
The quest for the right kernel in Bayesian impulse response identification: The use of OBFs. Autom. 87: 318-329 (2018) - [j52]Giulio Bottegal, Gianluigi Pillonetto:
The generalized cross validation filter. Autom. 90: 130-137 (2018) - [j51]Gianluigi Pillonetto:
System identification using kernel-based regularization: New insights on stability and consistency issues. Autom. 93: 321-332 (2018) - [j50]Tianshi Chen
On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses. Autom. 95: 529-533 (2018) - [j49]Mohamed Abdelmonim Hassan Darwish, Pepijn Bastiaan Cox
Prediction-error identification of LPV systems: A nonparametric Gaussian regression approach. Autom. 97: 92-103 (2018) - [j48]Aleksandr Y. Aravkin
Generalized System Identification with Stable Spline Kernels. SIAM J. Sci. Comput. 40(5): B1419-B1443 (2018) - [c63]Anna Scampicchio, Gianluigi Pillonetto:
A New Model Selection Approach to Hybrid Kernel-Based Estimation. CDC 2018: 3068-3073 - [c62]Giada Acciaroli, Andrea Facchinetti, Gianluigi Pillonetto, Giovanni Sparacino:
Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models. EMBC 2018: 3630-3633 - [c61]Anas W. Alhashimi, Simone Del Favero
Bayesian strategies for calibrating heteroskedastic static sensors with unknown model structures. ECC 2018: 2447-2453 - [c60]Algo Carè
Uncertainty Bounds for Kernel-based Regression: a Bayesian SPS Approach. MLSP 2018: 1-6 - 2017
- [j47]Giulia Prando, Alessandro Chiuso
Maximum Entropy vector kernels for MIMO system identification. Autom. 79: 326-339 (2017) - [j46]Marco Todescato
Multi-robots Gaussian estimation and coverage control: From client-server to peer-to-peer architectures. Autom. 80: 284-294 (2017) - [j45]Giulio Bottegal
A new kernel-based approach to system identification with quantized output data. Autom. 85: 145-152 (2017) - [j44]Aleksandr Y. Aravkin, James V. Burke, Lennart Ljung, Aurélie C. Lozano, Gianluigi Pillonetto:
Generalized Kalman smoothing: Modeling and algorithms. Autom. 86: 63-86 (2017) - [c59]Gianluigi Pillonetto, Luca Schenato, Damiano Varagnolo
Statistical bounds for Gaussian regression algorithms based on Karhunen-Loève expansions. CDC 2017: 363-368 - [i15]Marco Todescato, Andrea Carron, Ruggero Carli, Gianluigi Pillonetto, Luca Schenato:
Efficient Spatio-Temporal Gaussian Regression via Kalman Filtering. CoRR abs/1705.01485 (2017) - [i14]Giulio Bottegal, Gianluigi Pillonetto:
The Generalized Cross Validation Filter. CoRR abs/1706.02495 (2017) - [i13]Gianluigi Pillonetto, Luca Schenato, Damiano Varagnolo:
Distributed multi-agent Gaussian regression via Karhunen-Loève expansions. CoRR abs/1708.00194 (2017) - 2016
- [j43]Tianshi Chen
Maximum entropy properties of discrete-time first-order stable spline kernel. Autom. 66: 34-38 (2016) - [j42]Giulio Bottegal
Robust EM kernel-based methods for linear system identification. Autom. 67: 114-126 (2016) - [j41]Gianluigi Pillonetto, Tianshi Chen
Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint. Autom. 69: 137-149 (2016) - [j40]Gianluigi Pillonetto:
A new kernel-based approach to hybrid system identification. Autom. 70: 21-31 (2016) - [j39]Damiano Varagnolo
Newton-Raphson Consensus for Distributed Convex Optimization. IEEE Trans. Autom. Control. 61(4): 994-1009 (2016) - [c58]Andrea Carron, Marco Todescato
Machine learning meets Kalman Filtering. CDC 2016: 4594-4599 - [c57]Tianshi Chen, Gianluigi Pillonetto, Alessandro Chiuso, Lennart Ljung:
Continuous-time DC kernel - A stable generalized first order spline kernel. CDC 2016: 4647-4652 - [c56]Diego Romeres, Giulia Prando, Gianluigi Pillonetto, Alessandro Chiuso:
On-line Bayesian system identification. ECC 2016: 1359-1364 - [c55]Giulia Prando, Diego Romeres, Gianluigi Pillonetto, Alessandro Chiuso:
Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets. ECC 2016: 1365-1370 - [c54]Gianluigi Pillonetto, Aleksandr Y. Aravkin:
A stable spline convex approach to hybrid systems identification. MLSP 2016: 1-6 - [i12]Diego Romeres, Giulia Prando, Gianluigi Pillonetto, Alessandro Chiuso:
On-line Bayesian System Identification. CoRR abs/1601.04251 (2016) - [i11]Giulio Bottegal, Håkan Hjalmarsson, Gianluigi Pillonetto:
A new kernel-based approach to system identification with quantized output data. CoRR abs/1610.00470 (2016) - [i10]Gianluigi Pillonetto:
The interplay between system identification and machine learning. CoRR abs/1612.09158 (2016) - 2015
- [j38]Gianluigi Pillonetto, Alessandro Chiuso
Tuning complexity in regularized kernel-based regression and linear system identification: The robustness of the marginal likelihood estimator. Autom. 58: 106-117 (2015) - [j37]Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto:
The Connection Between Bayesian Estimation of a Gaussian Random Field and RKHS. IEEE Trans. Neural Networks Learn. Syst. 26(7): 1518-1524 (2015) - [c53]Mohamed Abdelmonim Hassan Darwish
Bayesian identification of LPV Box-Jenkins models. CDC 2015: 66-71 - [c52]Giulio Bottegal
Outlier robust kernel-based system identification using ℓ1-Laplace techniques. CDC 2015: 2109-2114 - [c51]Mohamed Abdelmonim Hassan Darwish
Perspectives of orthonormal basis functions based kernels in Bayesian system identification? CDC 2015: 2713-2718 - [c50]Tianshi Chen, Gianluigi Pillonetto, Alessandro Chiuso
Spectral analysis of the DC kernel for regularized system identification. CDC 2015: 4017-4022 - [c49]Damiano Varagnolo
Auto-tuning procedures for distributed nonparametric regression algorithms. ECC 2015: 640-647 - [c48]Diego Romeres, Gianluigi Pillonetto, Alessandro Chiuso:
Identification of stable models via nonparametric prediction error methods. ECC 2015: 2044-2049 - [c47]Andrea Carron, Marco Todescato
Multi-agents adaptive estimation and coverage control using Gaussian regression. ECC 2015: 2490-2495 - [c46]Gianluigi Pillonetto:
Identification of hybrid systems using stable spline kernels. MLSP 2015: 1-6 - [i9]Tianshi Chen, Tohid Ardeshiri, Francesca P. Carli, Alessandro Chiuso, Lennart Ljung, Gianluigi Pillonetto:
Maximum entropy properties of discrete-time first-order stable spline kernel. CoRR abs/1504.03253 (2015) - [i8]Giulio Bottegal, Gianluigi Pillonetto, Håkan Hjalmarsson:
Bayesian kernel-based system identification with quantized output data. CoRR abs/1504.06877 (2015) - [i7]Gianluigi Pillonetto, Tianshi Chen, Alessandro Chiuso, Giuseppe De Nicolao, Lennart Ljung:
Regularized linear system identification using atomic, nuclear and kernel-based norms: the role of the stability constraint. CoRR abs/1507.00564 (2015) - [i6]Giulia Prando, Gianluigi Pillonetto, Alessandro Chiuso:
Maximum Entropy Vector Kernels for MIMO system identification. CoRR abs/1508.02865 (2015) - 2014
- [j36]Gianluigi Pillonetto, Francesco Dinuzzo, Tianshi Chen
Kernel methods in system identification, machine learning and function estimation: A survey. Autom. 50(3): 657-682 (2014) - [j35]Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso, Gianluigi Pillonetto:
Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso. J. Mach. Learn. Res. 15(1): 217-252 (2014) - [j34]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Robust and Trend-Following Student's t Kalman Smoothers. SIAM J. Control. Optim. 52(5): 2891-2916 (2014) - [j33]Damiano Varagnolo
Distributed Cardinality Estimation in Anonymous Networks. IEEE Trans. Autom. Control. 59(3): 645-659 (2014) - [j32]Tianshi Chen
System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques. IEEE Trans. Autom. Control. 59(11): 2933-2945 (2014) - [c45]Tianshi Chen, Martin S. Andersen
Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method. CDC 2014: 265-270 - [c44]Giulia Prando, Alessandro Chiuso
Bayesian and regularization approaches to multivariable linear system identification: The role of rank penalties. CDC 2014: 1482-1487 - [c43]Alessandro Chiuso
On the design of multiple kernels for nonparametric linear system identification. CDC 2014: 3346-3351 - [c42]Alessandro Chiuso, Gianluigi Pillonetto:
Bayesian and nonparametric methods for system identification and model selection. ECC 2014: 2376-2381 - [c41]Gianluigi Pillonetto, Alessandro Chiuso:
Tuning complexity in kernel-based linear system identification: The robustness of the marginal likelihood estimator. ECC 2014: 2386-2391 - [c40]Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy, Gianluigi Pillonetto:
Kalman smoothing with persistent nuisance parameters. MLSP 2014: 1-6 - [c39]Gianluigi Pillonetto, Aleksandr Y. Aravkin:
A new kernel-based approach for identification of time-varying linear systems. MLSP 2014: 1-6 - [i5]Andrea Carron, Marco Todescato, Ruggero Carli, Luca Schenato, Gianluigi Pillonetto:
Multi-agents adaptive estimation and coverage control using Gaussian regression. CoRR abs/1407.5807 (2014) - [i4]Giulia Prando, Alessandro Chiuso, Gianluigi Pillonetto:
Bayesian and regularization approaches to multivariable linear system identification: the role of rank penalties. CoRR abs/1409.8327 (2014) - [i3]Giulio Bottegal, Aleksandr Y. Aravkin, Håkan Hjalmarsson, Gianluigi Pillonetto:
Robust EM kernel-based methods for linear system identification. CoRR abs/1411.5915 (2014) - 2013
- [j31]Gianluigi Pillonetto, Bradley M. Bell, Simone Del Favero
Distributed Kalman smoothing in static Bayesian networks. Autom. 49(4): 1001-1011 (2013) - [j30]Gianluigi Pillonetto:
Consistent identification of Wiener systems: A machine learning viewpoint. Autom. 49(9): 2704-2712 (2013) - [j29]Giulio Bottegal
Regularized spectrum estimation using stable spline kernels. Autom. 49(11): 3199-3209 (2013) - [j28]Costanza D'Avanzo, Anahita Goljahani, Gianluigi Pillonetto, Giuseppe De Nicolao, Giovanni Sparacino:
A multi-task learning approach for the extraction of single-trial evoked potentials. Comput. Methods Programs Biomed. 110(2): 125-136 (2013) - [j27]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Sparse/robust estimation and Kalman smoothing with nonsmooth log-concave densities: modeling, computation, and theory. J. Mach. Learn. Res. 14(1): 2689-2728 (2013) - [j26]Damiano Varagnolo
Finding Potential Support Vectors in Separable Classification Problems. IEEE Trans. Neural Networks Learn. Syst. 24(11): 1799-1813 (2013) - [c38]Gianluigi Pillonetto, Tianshi Chen, Lennart Ljung
Kernel-Based Model Order Selection for Linear System Identification. ALCOSP 2013: 257-262 - [c37]Tianshi Chen, Alessandro Chiuso
Rank-1 kernels for regularized system identification. CDC 2013: 5162-5167 - [c36]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Linear system identification using stable spline kernels and PLQ penalties. CDC 2013: 5168-5173 - [c35]Gianluigi Pillonetto, Tianshi Chen, Lennart Ljung:
Kernel-based model order selection for identification and prediction of linear dynamic systems. CDC 2013: 5174-5179 - [c34]Alessandro Chiuso
Regularization strategies for nonparametric system identification. CDC 2013: 6013-6018 - [i2]Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto:
The exact relationship between regularization in RKHS and Bayesian estimation of Gaussian random fields. CoRR abs/1301.5288 (2013) - 2012
- [j25]Gianluigi Pillonetto, Gorkem Erinc, Stefano Carpin:
Online Estimation of Covariance Parameters using Extended Kalman Filtering and Application to Robot Localization. Adv. Robotics 26(18): 2169-2188 (2012) - [j24]Alessandro Chiuso
A Bayesian approach to sparse dynamic network identification. Autom. 48(8): 1553-1565 (2012) - [j23]Damiano Varagnolo
Distributed parametric and nonparametric regression with on-line performance bounds computation. Autom. 48(10): 2468-2481 (2012) - [j22]Giorgio Quer, Riccardo Masiero, Gianluigi Pillonetto, Michele Rossi, Michele Zorzi:
Sensing, Compression, and Recovery for WSNs: Sparse Signal Modeling and Monitoring Framework. IEEE Trans. Wirel. Commun. 11(10): 3447-3461 (2012) - [c33]Filippo Zanella, Damiano Varagnolo
Multidimensional Newton-Raphson consensus for distributed convex optimization. ACC 2012: 1079-1084 - [c32]Damiano Varagnolo
Consensus based estimation of anonymous networks size using Bernoulli trials. ACC 2012: 2196-2201 - [c31]Giulio Bottegal
Regularized spectrum estimation in spaces induced by stable spline kernels. ACC 2012: 2695-2700 - [c30]Tianshi Chen
Sparse multiple kernels for impulse response estimation with majorization minimization algorithms. CDC 2012: 1500-1505 - [c29]Simone Del Favero
Bayesian learning of probability density functions: A Markov chain Monte Carlo approach. CDC 2012: 1512-1517 - [c28]Aleksandr Y. Aravkin, James V. Burke, Gianluigi Pillonetto:
Nonsmooth regression and state estimation using piecewise quadratic log-concave densities. CDC 2012: 4101-4106 - [c27]Filippo Zanella, Damiano Varagnolo
The convergence rate of Newton-Raphson consensus optimization for quadratic cost functions. CDC 2012: 5098-5103 - [c26]Ruggero Carli, Tianshi Chen
On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels. CDC 2012: 5260-5265 - 2011
- [j21]Gianluigi Pillonetto, Alessandro Chiuso
Prediction error identification of linear systems: A nonparametric Gaussian regression approach. Autom. 47(2): 291-305 (2011) - [j20]Gianluigi Pillonetto, Minh Ha Quang
A New Kernel-Based Approach for NonlinearSystem Identification. IEEE Trans. Autom. Control. 56(12): 2825-2840 (2011) - [j19]Aleksandr Y. Aravkin, Bradley M. Bell, James V. Burke, Gianluigi Pillonetto:
An 1 -Laplace Robust Kalman Smoother. IEEE Trans. Autom. Control. 56(12): 2898-2911 (2011) - [j18]Francesco Dinuzzo, Gianluigi Pillonetto, Giuseppe De Nicolao:
Client-Server Multitask Learning From Distributed Datasets. IEEE Trans. Neural Networks 22(2): 290-303 (2011) - [c25]Aleksandr Y. Aravkin, James V. Burke, Alessandro Chiuso
Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso. CDC/ECC 2011: 156-161 - [c24]Simone Del Favero
On the discardability of data in support vector classification problems. CDC/ECC 2011: 3210-3215 - [c23]Gianluigi Pillonetto, Giuseppe De Nicolao:
Kernel selection in linear system identification Part I: A Gaussian process perspective. CDC/ECC 2011: 4318-4325 - [c22]Filippo Zanella, Damiano Varagnolo
Newton-Raphson consensus for distributed convex optimization. CDC/ECC 2011: 5917-5922 - [c21]Francesco Dinuzzo, Cheng Soon Ong, Peter V. Gehler, Gianluigi Pillonetto:
Learning Output Kernels with Block Coordinate Descent. ICML 2011: 49-56 - 2010
- [j17]Gianluigi Pillonetto, Giuseppe De Nicolao:
A new kernel-based approach for linear system identification. Autom. 46(1): 81-93 (2010) - [j16]Gianluigi Pillonetto, Francesco Dinuzzo, Giuseppe De Nicolao:
Bayesian Online Multitask Learning of Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 32(2): 193-205 (2010) - [c20]Gianluigi Pillonetto, Alessandro Chiuso, Giuseppe De Nicolao:
Regularized estimation of sums of exponentials in spaces generated by stable spline kernels. ACC 2010: 498-503 - [c19]Damiano Varagnolo, Gianluigi Pillonetto, Luca Schenato:
Distributed consensus-based Bayesian estimation: sufficient conditions for performance characterization. ACC 2010: 3986-3991 - [c18]Damiano Varagnolo
Distributed statistical estimation of the number of nodes in sensor networks. CDC 2010: 1498-1503 - [c17]Alessandro Chiuso
Nonparametric sparse estimators for identification of large scale linear systems. CDC 2010: 2942-2947 - [c16]Gianluigi Pillonetto, Aleksandr Y. Aravkin, Stefano Carpin:
The unconstrained and inequality constrained moving horizon approach to robot localization. IROS 2010: 3830-3835 - [c15]Alessandro Chiuso, Gianluigi Pillonetto:
Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors. NIPS 2010: 397-405
2000 – 2009
- 2009
- [j15]Bradley M. Bell, James V. Burke, Gianluigi Pillonetto:
An inequality constrained nonlinear Kalman-Bucy smoother by interior point likelihood maximization. Autom. 45(1): 25-33 (2009) - [j14]Gianluigi Pillonetto, Giuseppe De Nicolao, Marco Chierici
Fast algorithms for nonparametric population modeling of large data sets. Autom. 45(1): 173-179 (2009) - [j13]Gianluigi Pillonetto, Alessandro Chiuso
Fast computation of smoothing splines subject to equality constraints. Autom. 45(12): 2842-2849 (2009) - [j12]Francesca Zanderigo
Nonlinear Stochastic Regularization to Characterize Tissue Residue Function in Bolus-Tracking MRI: Assessment and Comparison With SVD, Block-Circulant SVD, and Tikhonov. IEEE Trans. Biomed. Eng. 56(5): 1287-1297 (2009) - [c14]Gianluigi Pillonetto, Alessandro Chiuso
A Bayesian learning approach to linear system identification with missing data. CDC 2009: 4698-4703 - [c13]Damiano Varagnolo
Distributed function and time delay estimation using nonparametric techniques. CDC 2009: 7608-7613 - 2008
- [j11]Gianluigi Pillonetto, Bradley M. Bell:
Optimal smoothing of non-linear dynamic systems via Monte Carlo Markov chains. Autom. 44(7): 1676-1685 (2008) - [j10]Gianluigi Pillonetto:
Solutions of nonlinear control and estimation problems in reproducing kernel Hilbert spaces: Existence and numerical determination. Autom. 44(8): 2135-2141 (2008) - [j9]Eugenio Cinquemani, Gianluigi Pillonetto:
Wavelet estimation by Bayesian thresholding and model selection. Autom. 44(9): 2288-2297 (2008) - [j8]Gianluigi Pillonetto:
Identification of Time-Varying Systems in Reproducing Kernel Hilbert Spaces. IEEE Trans. Autom. Control. 53(9): 2202-2209 (2008) - [c12]Gianluigi Pillonetto, Claudio Cobelli:
Predictive power of indices derived from models of biological dynamic systems. ACC 2008: 2124-2129 - [c11]Giuseppe De Nicolao, Gianluigi Pillonetto:
A new kernel-based approach for system identification. ACC 2008: 4510-4516 - [c10]Gianluigi Pillonetto, Francesco Dinuzzo, Giuseppe De Nicolao:
Bayesian online multi-task learning using regularization networks. ACC 2008: 4517-4522 - [c9]Gianluigi Pillonetto, Alessandro Chiuso
Predictor estimation via Gaussian regression. CDC 2008: 744-749 - [c8]Alessandro Chiuso
Subspace identification using predictor estimation via Gaussian regression. CDC 2008: 3299-3304 - [c7]Gorkem Erinc, Gianluigi Pillonetto, Stefano Carpin:
Online estimation of variance parameters: Experimental results with applications to localization. IROS 2008: 1890-1895 - [i1]Francesco Dinuzzo, Gianluigi Pillonetto, Giuseppe De Nicolao:
Client-server multi-task learning from distributed datasets. CoRR abs/0812.4235 (2008) - 2007
- [j7]Gianluigi Pillonetto, Claudio Cobelli:
Identifiability of the stochastic semi-blind deconvolution problem for a class of time-invariant linear systems. Autom. 43(4): 647-654 (2007) - [j6]Gianluigi Pillonetto, Bradley M. Bell:
Bayes and empirical Bayes semi-blind deconvolution using eigenfunctions of a prior covariance. Autom. 43(10): 1698-1712 (2007) - [c6]Giuseppe De Nicolao, Gianluigi Pillonetto, Marco Chierici
Efficient Nonparametric Population Modeling for Large Data Sets. ACC 2007: 2921-2926 - [c5]Gianluigi Pillonetto, Stefano Carpin:
Multirobot localization with unknown variance parameters using iterated Kalman filtering. IROS 2007: 1709-1714 - 2006
- [j5]Gianluigi Pillonetto, Maria Pia Saccomani
Input estimation in nonlinear dynamical systems using differential algebra techniques. Autom. 42(12): 2117-2129 (2006) - [j4]Gianluigi Pillonetto, Andrea Caumo, Giovanni Sparacino, Claudio Cobelli:
A new dynamic index of insulin sensitivity. IEEE Trans. Biomed. Eng. 53(3): 369-379 (2006) - [c4]Marco Chierici
Glucose Production by Deconvolution in Intravenous and Oral Glucose Tolerance Tests: Role of Output Variable. EMBC 2006: 5045-5048 - 2005
- [j3]Stefano Carpin, Gianluigi Pillonetto:
Motion planning using adaptive random walks. IEEE Trans. Robotics 21(1): 129-136 (2005) - [c3]Stefano Carpin, Gianluigi Pillonetto:
Merging the adaptive random walks planner with the randomized potential field planner. RoMoCo 2005: 151-156 - 2003
- [c2]Stefano Carpin, Gianluigi Pillonetto:
Robot motion planning using adaptive random walks. ICRA 2003: 3809-3814 - [c1]Gianluigi Pillonetto, Bradley M. Bell:
Bayesian Deconvolution of Functions in RKHS Using MCMC Techniques. System Modelling and Optimization 2003: 257-268 - 2002
- [j2]Giovanni Sparacino, Gianluigi Pillonetto, Massimo Capello, Giuseppe De Nicolao, Claudio Cobelli:
WINSTODEC: a stochastic deconvolution interactive program for physiological and pharmacokinetic systems. Comput. Methods Programs Biomed. 67(1): 67-77 (2002) - 2001
- [j1]Gianluigi Pillonetto, Giovanni Sparacino, Claudio Cobelli:
Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method. IEEE Trans. Biomed. Eng. 48(11): 1352-1354 (2001)
Coauthor Index
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