Author:
Mu Biqiang,Ljung Lennart,Chen Tianshi
Funder
Recruitment Program of Global Experts
Shenzhen Science and Technology Innovation Commission
National Key Research and Development Program of China
National Key Research and Development Program of China Stem Cell and Translational Research
Shenzhen Municipal Science and Technology Innovation Council
National Natural Science Foundation of China
Subject
Electrical and Electronic Engineering,Control and Systems Engineering
Reference36 articles.
1. Aravkin, A., Burke, J. V., Chiuso, A., & Pillonetto, G. (2012a). On the estimation of hyperparameters for empirical Bayes estimators: Maximum marginal likelihood vs minimum MSE. In Proceeding of the IFAC symposium on system identification (pp. 125–130).
2. Aravkin, A., Burke, J. V., Chiuso, A., & Pillonetto, G. (2012b). On the MSE properties of empirical Bayes methods for sparse estimation. In Proceeding of the IFAC symposium on system identification (pp. 965–970).
3. Convex vs non-convex estimators for regression and sparse estimation: the mean squared error properties of ARD and GLasso;Aravkin;Journal of Machine Learning Research,2014
4. On the mathematical foundations of stable RKHSs;Bisiacco;Automatica,2020
5. Maximum entropy kernels for system identification;Carli;IEEE Transactions on Automatic Control,2017