Tianshi Chen
Orcid: 0000-0001-8655-2655Affiliations:
- Chinese University of Hong Kong, School of Data Science, Hong Kong
- Chinese University of Hong Kong,School of Science and Engineering, Hong Kong (2015 - 2020)
- Linköping University, Department of Electrical Engineering, Sweden (2009 - 2015)
- Chinese University of Hong Kong, Hong Kong (PhD 2008)
- Harbin Institute of Technology, China (former)
According to our database1,
Tianshi Chen
authored at least 86 papers
between 2004 and 2024.
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Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
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On csauthors.net:
Bibliography
2024
A Family of Hyperparameter Estimators Linking EB and SURE for Kernel-Based Regularization Methods.
IEEE Trans. Autom. Control., December, 2024
Distributed Iterative Learning Control of Nonlinear Multiagent Systems Using Controller-Based Dynamic Linearization Method.
IEEE Trans. Cybern., August, 2024
On Asymptotic Optimality of Cross-Validation Estimators for Kernel-Based Regularized System Identification.
IEEE Trans. Autom. Control., July, 2024
When cannot regularization improve the least squares estimate in the kernel-based regularized system identification.
Autom., February, 2024
Autom., January, 2024
CoRR, 2024
A Local Gaussian Process Regression Approach to Frequency Response Function Estimation.
CoRR, 2024
A Class of Convex Optimization-Based Recursive Algorithms for Identification of Stochastic Systems.
CoRR, 2024
2023
Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyperparameter Estimator.
IEEE Trans. Autom. Control., December, 2023
Data-Driven Distributed Adaptive Consensus Tracking of Nonlinear Multiagent Systems: A Controller-Based Dynamic Linearization Method.
IEEE Trans. Syst. Man Cybern. Syst., November, 2023
Input Design for Regularized System Identification: Stationary Conditions and Sphere Preserving Algorithm.
IEEE Trans. Autom. Control., September, 2023
Kernel-based regularized iterative learning control of repetitive linear time-varying systems.
Autom., August, 2023
Identifiability Analysis of Noise Covariances for LTI Stochastic Systems With Unknown Inputs.
IEEE Trans. Autom. Control., July, 2023
An efficient implementation for spatial-temporal Gaussian process regression and its applications.
Autom., 2023
On embeddings and inverse embeddings of input design for regularized system identification.
Autom., 2023
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
An Efficient Implementation for Kernel-Based Regularized System Identification with Periodic Input Signals.
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
Proceedings of the 62nd IEEE Conference on Decision and Control, 2023
2022
The noise covariances of linear Gaussian systems with unknown inputs are not uniquely identifiable using autocovariance least-squares.
Syst. Control. Lett., 2022
Asymptotic Theory for Regularized System Identification Part I: Empirical Bayes Hyper-parameter Estimator.
CoRR, 2022
2021
Tutorial on Asymptotic Properties of Regularized Least Squares Estimator for Finite Impulse Response Model.
CoRR, 2021
Identification of Switched Linear Systems: Persistence of Excitation and Numerical Algorithms.
CoRR, 2021
On semiseparable kernels and efficient implementation for regularized system identification and function estimation.
Autom., 2021
Bus arrival time prediction and reliability analysis: An experimental comparison of functional data analysis and Bayesian support vector regression.
Appl. Soft Comput., 2021
On Asymptotic Distribution of Generalized Cross Validation Hyper-parameter Estimator for Regularized System Identification<sup>*</sup>.
Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021
2020
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series.
IEEE Trans. Signal Process., 2020
SIAM J. Matrix Anal. Appl., 2020
CoRR, 2020
On Effects of Condition Number of Regression Matrix upon Hyper-parameter Estimators for Kernel-based Regularization Methods.
CoRR, 2020
Regularized LTI system identification in the presence of outliers: A variational EM approach.
Autom., 2020
On the Influence of Ill-conditioned Regression Matrix on Hyper-parameter Estimators for Kernel-based Regularization Methods.
Proceedings of the 59th IEEE Conference on Decision and Control, 2020
2019
IEEE Trans. Signal Process., 2019
Distributed Gaussian Processes Hyperparameter Optimization for Big Data Using Proximal ADMM.
IEEE Signal Process. Lett., 2019
Linear Multiple Low-Rank Kernel Based Stationary Gaussian Processes Regression for Time Series.
CoRR, 2019
Parameter estimation of discrete-time sinusoidal signals: A nonlinear control approach.
Autom., 2019
Recursive Implementation of Gaussian Process Regression for Spatial-Temporal Data Modeling.
Proceedings of the 11th International Conference on Wireless Communications and Signal Processing, 2019
2018
IEEE Trans. Autom. Control., 2018
On asymptotic properties of hyperparameter estimators for kernel-based regularization methods.
Autom., 2018
Autom., 2018
On the stability of reproducing kernel Hilbert spaces of discrete-time impulse responses.
Autom., 2018
Sparse Structure Enabled Grid Spectral Mixture Kernel for Temporal Gaussian Process Regression.
Proceedings of the 21st International Conference on Information Fusion, 2018
Asymptotic Properties of Hyperparameter Estimators by Using Cross-Validations for Regularized System Identification.
Proceedings of the 57th IEEE Conference on Decision and Control, 2018
2017
On the input design for kernel-based regularized LTI system identification: Power-constrained inputs.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017
2016
Regularized linear system identification using atomic, nuclear and kernel-based norms: The role of the stability constraint.
Autom., 2016
Transfer function and transient estimation by Gaussian process regression in the frequency domain.
Autom., 2016
Autom., 2016
Proceedings of the 55th IEEE Conference on Decision and Control, 2016
2015
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015
Proceedings of the 14th European Control Conference, 2015
Proceedings of the 54th IEEE Conference on Decision and Control, 2015
2014
System Identification Via Sparse Multiple Kernel-Based Regularization Using Sequential Convex Optimization Techniques.
IEEE Trans. Autom. Control., 2014
CoRR, 2014
Kernel methods in system identification, machine learning and function estimation: A survey.
Autom., 2014
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
Implementation of algorithms for tuning parameters in regularized least squares problems in system identification.
Autom., 2013
Proceedings of the 10th IEEE International Conference on Control and Automation, 2013
Kernel-based model order selection for identification and prediction of linear dynamic systems.
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Proceedings of the 52nd IEEE Conference on Decision and Control, 2013
Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013
Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, 2013
2012
On the estimation of transfer functions, regularizations and Gaussian processes - Revisited.
Autom., 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
IEEE Trans. Signal Process., 2011
Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, 2011
2010
A small gain approach to global stabilization of nonlinear feedforward systems with input unmodeled dynamics.
Autom., 2010
Comments on "State estimation for linear systems with state equality constraints" [Automatica 43 (2007) 1363-1368].
Autom., 2010
Proceedings of the 49th IEEE Conference on Decision and Control, 2010
2009
IEEE Trans. Autom. Control., 2009
2008
IEEE Trans. Autom. Control., 2008
Global robust stabilization of nonlinear strict feedforward systems with input unmodeled dynamics.
Proceedings of the American Control Conference, 2008
2007
Proceedings of the 46th IEEE Conference on Decision and Control, 2007
2005
Proceedings of the American Control Conference, 2005
2004
Proceedings of the 8th International Conference on Control, 2004