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Low-rank matrix recovery from noise via an mdl framework-based atomic norm Journal article
Qin, Anyong, Xian, Lina, Yang, Yongliang, Zhang, Taiping, Yan Tang, Yuan. Low-rank matrix recovery from noise via an mdl framework-based atomic norm[J]. Sensors (Switzerland), 2020, 20(21), 1-21.
Authors:  Qin, Anyong;  Xian, Lina;  Yang, Yongliang;  Zhang, Taiping;  Yan Tang, Yuan
Favorite | TC[WOS]:3 TC[Scopus]:3  IF:3.4/3.7 | Submit date：2021/12/06
Atomic Norm  Low-rank Matrix Recovery  Minimum Description Length Principle  Robust Principal Components Analysis  
Covariance matrix estimation with multi-regularization parameters based on MDL principle Journal article
Zhou X., Guo P., Chen C.L.P.. Covariance matrix estimation with multi-regularization parameters based on MDL principle[J]. Neural Processing Letters, 2013, 38(2), 227-238.
Authors:  Zhou X.;  Guo P.;  Chen C.L.P.
Favorite | TC[WOS]:5 TC[Scopus]:5 | Submit date：2019/02/11
Covariance Matrix Estimation  Gaussian Classifier  Minimum Description Length Principle  Multi-regularization Parameters Selection  
Multi-regularization parameters estimation for Gaussian mixture classifier based on MDL principle Conference paper
Zhou X., Guo P., Philip Chen C.L.. Multi-regularization parameters estimation for Gaussian mixture classifier based on MDL principle[C], 2011, 112-117.
Authors:  Zhou X.;  Guo P.;  Philip Chen C.L.
Favorite |  | Submit date：2019/02/11
Covariance matrix estimation  Gaussian classifier  Minimum description length  Multi-regularization parameters selection