Alessandro Chiuso

According to our database1, Alessandro Chiuso authored at least 90 papers between 1997 and 2019.

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Bibliography

2019
Stable spline identification of linear systems under missing data.
Automatica, 2019

2018
Derivative-free online learning of inverse dynamics models.
CoRR, 2018

The role of noise modeling in the estimation of resting-state brain effective connectivity.
CoRR, 2018

The harmonic analysis of kernel functions.
Automatica, 2018

CoRe: Control-oriented Regularization for System Identification.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017
Feedback Control Over Lossy SNR-Limited Channels: Linear Encoder-Decoder-Controller Design.
IEEE Trans. Automat. Contr., 2017

Sparse plus low rank network identification: A nonparametric approach.
Automatica, 2017

Maximum Entropy vector kernels for MIMO system identification.
Automatica, 2017

Estimating effective connectivity in linear brain network models.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016
Modeling Visual Representations: Defining Properties and Deep Approximations
Proceedings of the 4th International Conference on Learning Representations, 2016

Online semi-parametric learning for inverse dynamics modeling.
CoRR, 2016

Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint.
Automatica, 2016

Maximum entropy properties of discrete-time first-order stable spline kernel.
Automatica, 2016

Regularization and Bayesian learning in dynamical systems: Past, present and future.
Annual Reviews in Control, 2016

On-line Bayesian system identification.
Proceedings of the 2016 European Control Conference, 2016

Virtual reference feedback tuning with Bayesian regularization.
Proceedings of the 2016 European Control Conference, 2016

Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets.
Proceedings of the 2016 European Control Conference, 2016

Online semi-parametric learning for inverse dynamics modeling.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Online identification of time-varying systems: A Bayesian approach.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

Continuous-time DC kernel - A stable generalized first order spline kernel.
Proceedings of the 55th IEEE Conference on Decision and Control, 2016

2015
System Identification Techniques: Convexification, Regularization, and Relaxation.
Proceedings of the Encyclopedia of Systems and Control, 2015

A Scaled Gradient Projection Method for Bayesian Learning in Dynamical Systems.
SIAM J. Scientific Computing, 2015

Visual Scene Representations: Sufficiency, Minimality, Invariance and Deep Approximations.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Tuning complexity in regularized kernel-based regression and linear system identification: The robustness of the marginal likelihood estimator.
Automatica, 2015

Robust inference for visual-inertial sensor fusion.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Identification of stable models via nonparametric prediction error methods.
Proceedings of the European Control Conference, 2015

Linear encoder-decoder-controller design over channels with packet loss and quantization noise.
Proceedings of the European Control Conference, 2015

Texture representations for image and video synthesis.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2015

A Bayesian approach to sparse plus low rank network identification.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Model reduction for linear bayesian system identification.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

Spectral analysis of the DC kernel for regularized system identification.
Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2014
Remote Estimation With Noisy Measurements Subject to Packet Loss and Quantization Noise.
IEEE Trans. Control of Network Systems, 2014

System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques.
IEEE Trans. Automat. Contr., 2014

Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso.
J. Mach. Learn. Res., 2014

LQG-like control of scalar systems over communication channels: The role of data losses, delays and SNR limitations.
Automatica, 2014

Tuning complexity in kernel-based linear system identification: The robustness of the marginal likelihood estimator.
Proceedings of the European Control Conference, 2014

Bayesian and nonparametric methods for system identification and model selection.
Proceedings of the European Control Conference, 2014

Bayesian and regularization approaches to multivariable linear system identification: The role of rank penalties.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

On the design of multiple kernels for nonparametric linear system identification.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

Anomaly detection in homogenous populations: A sparse multiple kernel-based regularization method.
Proceedings of the 53rd IEEE Conference on Decision and Control, 2014

2013
Control recognition bounds for visual learning and exploration.
Proceedings of the 2013 Information Theory and Applications Workshop, 2013

LQG cheap control subject to packet loss and SNR limitations.
Proceedings of the European Control Conference, 2013

Texture Compression.
Proceedings of the 2013 Data Compression Conference, 2013

Remote estimation subject to packet loss and quantization noise.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

LQG cheap control over SNR-limited lossy channels with delay.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Regularization strategies for nonparametric system identification.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

Rank-1 kernels for regularized system identification.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013

2012
A Bayesian approach to sparse dynamic network identification.
Automatica, 2012

Controlled Recognition Bounds for Visual Learning and Exploration.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Sparse multiple kernels for impulse response estimation with majorization minimization algorithms.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

On the estimation of hyperparameters for Bayesian system identification with exponentially decaying kernels.
Proceedings of the 51th IEEE Conference on Decision and Control, 2012

2011
A New Kernel-Based Approach for NonlinearSystem Identification.
IEEE Trans. Automat. Contr., 2011

Optimal Synchronization for Networks of Noisy Double Integrators.
IEEE Trans. Automat. Contr., 2011

Gossip Algorithms for Simultaneous Distributed Estimation and Classification in Sensor Networks.
J. Sel. Topics Signal Processing, 2011

Prediction error identification of linear systems: A nonparametric Gaussian regression approach.
Automatica, 2011

Information fusion strategies and performance bounds in packet-drop networks.
Automatica, 2011

Controlled Recognition Bounds for Scaling and Occlusion Channels.
Proceedings of the 2011 Data Compression Conference (DCC 2011), 2011

Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso.
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011

2010
Dynamic Calibration of Adaptive Optics Systems: A System Identification Approach.
IEEE Trans. Contr. Sys. Techn., 2010

On the Asymptotic Properties of Closed-Loop CCA-Type Subspace Algorithms: Equivalence Results and Role of the Future Horizon.
IEEE Trans. Automat. Contr., 2010

Learning sparse dynamic linear systems using stable spline kernels and exponential hyperpriors.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

Nonparametric sparse estimators for identification of large scale linear systems.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Sparse calibration of an extreme Adaptive Optics system.
Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009
Fast computation of smoothing splines subject to equality constraints.
Automatica, 2009

Performance bounds for information fusion strategies in packet-drop networks.
Proceedings of the European Control Conference, 2009

A Bayesian learning approach to linear system identification with missing data.
Proceedings of the 48th IEEE Conference on Decision and Control, 2009

2008
Distributed Kalman filtering based on consensus strategies.
IEEE Journal on Selected Areas in Communications, 2008

Predictor estimation via Gaussian regression.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

Information fusion strategies from distributed filters in packet-drop networks.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

Subspace identification using predictor estimation via Gaussian regression.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

Some identification techniques in computer vision.
Proceedings of the 47th IEEE Conference on Decision and Control, 2008

2007
On the Relation Between CCA and Predictor-Based Subspace Identification.
IEEE Trans. Automat. Contr., 2007

Classification and Recognition of Dynamical Models: The Role of Phase, Independent Components, Kernels and Optimal Transport.
IEEE Trans. Pattern Anal. Mach. Intell., 2007

The role of vector autoregressive modeling in predictor-based subspace identification.
Automatica, 2007

Distributed Kalman filtering using consensus strategies.
Proceedings of the 46th IEEE Conference on Decision and Control, 2007

2006
Asymptotic variance of closed-loop subspace identification methods.
IEEE Trans. Automat. Contr., 2006

Non Linear Temporal Textures Synthesis: A Monte Carlo Approach.
Proceedings of the Computer Vision, 2006

2005
Consistency analysis of some closed-loop subspace identification methods.
Automatica, 2005

2004
Asymptotic variance of subspace methods by data orthogonalization and model decoupling: a comparative analysis.
Automatica, 2004

Subspace identification by data orthogonalization and model decoupling.
Automatica, 2004

Numerical conditioning and asymptotic variance of subspace estimates.
Automatica, 2004

On the ill-conditioning of subspace identification with inputs.
Automatica, 2004

Modeling and Synthesis of Facial Motion Driven by Speech.
Proceedings of the Computer Vision, 2004

2003
Dynamic Textures.
International Journal of Computer Vision, 2003

Observability of Linear Hybrid Systems.
Proceedings of the Hybrid Systems: Computation and Control, 2003

2002
Structure from Motion Causally Integrated Over Time.
IEEE Trans. Pattern Anal. Mach. Intell., 2002

2001
Recognition of Human Gaits.
Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2001), 2001

2000
Optimal Structure from Motion: Local Ambiguities and Global Estimates.
International Journal of Computer Vision, 2000

3-D Motion and Structure from 2-D Motion Causally Integrated over Time: Implementation.
Proceedings of the Computer Vision - ECCV 2000, 6th European Conference on Computer Vision, Dublin, Ireland, June 26, 2000

1997
Visual tracking of points as estimation on the unit sphere.
Proceedings of the confluence of vision and control, 1997


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