CHIUSO, ALESSANDRO
 Distribuzione geografica
Continente #
NA - Nord America 8152
EU - Europa 666
AS - Asia 402
Continente sconosciuto - Info sul continente non disponibili 3
OC - Oceania 2
Totale 9225
Nazione #
US - Stati Uniti d'America 8148
CN - Cina 330
FI - Finlandia 196
IT - Italia 140
UA - Ucraina 119
DE - Germania 101
SE - Svezia 69
VN - Vietnam 62
GB - Regno Unito 23
NL - Olanda 6
IN - India 5
CA - Canada 4
RU - Federazione Russa 4
CH - Svizzera 3
EU - Europa 3
MD - Moldavia 2
NZ - Nuova Zelanda 2
TR - Turchia 2
HK - Hong Kong 1
IR - Iran 1
LU - Lussemburgo 1
NO - Norvegia 1
RO - Romania 1
SG - Singapore 1
Totale 9225
Città #
Fairfield 1633
Woodbridge 1206
Houston 857
Ann Arbor 677
Jacksonville 633
Seattle 628
Ashburn 610
Wilmington 589
Cambridge 551
Princeton 197
San Diego 171
Medford 129
Nanjing 83
Helsinki 63
Dong Ket 62
Padova 54
Beijing 51
Des Moines 45
Shenyang 36
Hebei 27
Nanchang 21
Jiaxing 20
Changsha 18
Roxbury 14
Tianjin 14
Norwalk 12
Cittadella 11
Chandler 10
Ningbo 9
Jinan 8
Zhengzhou 8
Lanzhou 7
Redwood City 7
Borås 6
Guangzhou 6
Piove Di Sacco 6
Taizhou 6
London 5
Hangzhou 4
Rockville 4
Saint Petersburg 4
Belluno 3
Bengaluru 3
Milan 3
New York 3
Redmond 3
Zurich 3
Chisinau 2
Gorizia 2
Hanover 2
Monmouth Junction 2
Pinehaven 2
Rovigo 2
San Francisco 2
Simi Valley 2
Yellow Springs 2
Yenibosna 2
Ardabil 1
Calgary 1
Central 1
Enschede 1
Foshan 1
Geislingen an der Steige 1
Gothenburg 1
Groningen 1
Haikou 1
Indiana 1
Luxembourg 1
Montebelluna 1
Montréal 1
Morbegno 1
Mumbai 1
Nagold 1
Northfield 1
Nuoro 1
Orange 1
Ravenna 1
Rome 1
Shanghai 1
Singapore 1
Thiene 1
Walnut 1
Totale 8565
Nome #
Optimal Structure From Motion: Local Ambiguities and Global Estimates 120
Derivative-Free Online Learning of Inverse Dynamics Models 109
Dynamic Calibration of Adaptive Optics Systems: A System Identification Approach 104
Structure from Motion Causally Integrated over Time 102
A Bayesian approach to sparse dynamic network identification 102
A PI Consensus Controller for Networked Clocks Synchronization 98
On the relation between CCA and predictor-based subspace identification 97
Distributed Kalman filtering based on consensus strategies 96
Information fusion strategies and performance bounds in packet-drop networks 94
On the Ill-conditioning of subspace identification with inputs 92
Maximum entropy properties of discrete-time first-order stable spline kernel 90
Asymptotic variance of subspace methods by data orthogonalization andmodel decoupling: a comparative analysis 89
Regularization and Bayesian learning in dynamical systems: Past, present and future 89
Stable spline identification of linear systems under missing data 89
Monte Carlo filtering on Lie Groups 88
Anomaly detection in homogenous populations: a sparse multiple kernel-based regularization method 88
Efficient algorithms for large scale linear system identification using stable spline estimators 87
LQG-like control of scalar systems over communication channels: The role of data losses, delays and SNR limitations 87
The harmonic analysis of kernel functions 85
Fast computation of smoothing splines subject to equality constraints 84
Spectral analysis of the DC kernel for regularized system identification 84
System Identification: A Machine Learning Perspective 84
Modeling and synthesis of facial motion driven by speech 83
Prediction error identification of linear systems: A nonparametric Gaussian regression approach 83
Information fusion strategies from distributed filters in packet-drop networks 82
Maximum Entropy Vector Kernels for MIMO system identification 82
Gossip Algorithms for Simultaneous Distributed Estimation and Classification in Sensor Networks 81
Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint 81
CoRe: Control-oriented Regularization for System Identification 81
The Role of Vector Autoregressive Modeling in Predictor Based Subspace Identification 80
On the design of Multiple Kernels for nonparametric linear system identification 79
Tuning complexity in regularized kernel-based regression and linear system identification: The robustness of the marginal likelihood estimator 79
Predictor estimation via Gaussian regression 78
On the estimation of hyperparameters for Empirical Bayes estimators: Maximum Marginal Likelihood vs Minimum MSE 77
A Bayesian Approach to Sparse plus Low rank Network Identification 77
Tuning complexity in kernel-based linear system identification: the robustness of the marginal likelihood estimator 76
Robust inference for visual-inertial sensor fusion 76
LQG cheap control subject to packet loss and SNR limitations 75
Consistency Analysis of some Closed-Loop Subspace Identification Methods 75
The role of rank penalties in linear system identification 75
Sparse Calibration of an Extreme Adaptive Optics System 74
Observability and Identifiability of Jump Linear Systems 72
Applications of Hybrid System Identification in Computer Vision 72
Dynamic Calibration of Adaptive Optics Systems: A System Identification Approach 71
Constructing the state of Random Processes with Feedback 71
Asymptotic Variance of Closed-Loop Subspace Identification Methods 71
A New Kernel-Based Approach for NonlinearSystem Identification 71
A wide-sense estimation theory on the unit sphere 70
A SCALED GRADIENT PROJECTION METHOD FOR BAYESIAN LEARNING IN DYNAMICAL SYSTEMS 70
Classification and Recognition of Dynamical Models: The Role of Phase, Independent Components, Kernels and Optimal Transport 70
Optimal Synchronization for Networks of Noisy Double Integrators 70
Linear encoder-decoder-controller design over channels with packet loss and quantization noise 70
Observability Linear Hybrid Systems 69
Integration of Shape Constraints in Data Association Filters 69
LQG cheap control over SNR-limited lossy channels with delay 69
Online semi-parametric learning for inverse dynamics modeling 69
null 69
Sensor fusion and estimation strategies for data traffic reduction in rooted wireless sensor networks 68
Subspace Identification by orthogonal decomposition 68
Rank-1 kernels for regularized system identification 68
Identification of stable models via nonparametric prediction error methods 68
Classical vs. Bayesian methods for linear system identification: Point estimators and confidence sets 68
Convex vs nonconvex approaches for sparse estimation: Lasso, Multiple Kernel Learning and Hyperparameter Lasso 68
Remote estimation subject to packet loss and quantization noise 68
A note on estimation using quantized data 67
Simultaneous distributed estimation and classification in sensor networks 66
Regularization strategies for nonparametric system identification 65
Asymptotic Variance of Subspace Estimates 65
Regularization and Bayesian Learning in Dynamical Systems: Past, Present and Future 65
Virtual reference feedback tuning with Bayesian regularization 65
Snippets of System Identification in Computer Vision 64
Observability of Linear Hybrid Systems 64
Subspace identification using predictor estimation via Gaussian regression 64
The Role of Vector Autoregressive Modeling in Predictor Based Subspace Identification 63
A Bayesian learning approach to linear system identification with missing data 63
Remote estimation with noisy measurements subject to packet loss and quantization noise. 63
Estimating effective connectivity in linear brain network models 63
The role of noise modeling in the estimation of resting-state brain effective connectivity 63
Comparison of Two Subspace Identification Methods for Combined Deterministic -Stochastic Systems 62
Probing Inputs for Subspace Identification 62
Texture Representations for Image and Video Synthesis 62
Regularized estimation of sums of exponentials in spaces generated by stable spline kernels 61
Gossip algorithms for distributed ranking 61
Non Linear Temporal Textures Synthesis: A Monte Carlo Approach 61
Sparse DCM for whole-brain effective connectivity from resting-state fMRI data 60
Asymptotic Equivalence of Certain Closed-Loop Subspace Identification Methods 59
Performance bounds for information fusion strategies in packet-drop networks 59
Prediction error vs. subspace methods in closed loop identification 59
Error Analysis of Certain Subspace Methods 59
Estimating the Asymptotic Variance of Closed-Loop Subspace Estimators 59
Gaussian Processes for Wiener-Hammerstein System Identification 58
Sparse multiple kernels for impulse response estimation with majorization minimization algorithms 58
Controlled Recognition Bounds for Scaling and Occlusion Channels 58
Encoding scene structures for video compression 58
Subspace identification by data orthogonalization and model decoupling 57
Model reduction for linear Bayesian System Identification 57
Nonlinear system identification via Gaussian regression and mixtures of kernels 56
Wide-sense Estimation on the Special Orthogonal Group 56
3-D Motion and Structure Causally Integrated Over Time: Theory 56
Online identification of time-varying systems: A Bayesian approach 56
Totale 7345
Categoria #
all - tutte 13161
article - articoli 4316
book - libri 17
conference - conferenze 0
curatela - curatele 79
other - altro 66
patent - brevetti 0
selected - selezionate 0
volume - volumi 494
Totale 18133


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2017/2018196 0000 018 6710 30980
2018/20191347 401393 13 269 5232473416
2019/20202643 3878143249 301235 245316 29127597123
2020/20211610 7214629127 84155 103168 285120193128
2021/20221813 5818031698 10161 96224 9442272271
2022/2023314 28613114 00 00 0000
Totale 9357