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Items: 1 to 20 of 118

1.

Regularized matrix regression.

Zhou H, Li L.

J R Stat Soc Series B Stat Methodol. 2014 Mar 1;76(2):463-483.

2.

Regularized estimation of large-scale gene association networks using graphical Gaussian models.

Krämer N, Schäfer J, Boulesteix AL.

BMC Bioinformatics. 2009 Nov 24;10:384. doi: 10.1186/1471-2105-10-384.

3.

NETWORK-REGULARIZED HIGH-DIMENSIONAL COX REGRESSION FOR ANALYSIS OF GENOMIC DATA.

Sun H, Lin W, Feng R, Li H.

Stat Sin. 2014 Jul;24(3):1433-1459.

4.

Tensor Regression with Applications in Neuroimaging Data Analysis.

Zhou H, Li L, Zhu H.

J Am Stat Assoc. 2013;108(502):540-552.

5.

Spectral Regularization Algorithms for Learning Large Incomplete Matrices.

Mazumder R, Hastie T, Tibshirani R.

J Mach Learn Res. 2010 Mar 1;11:2287-2322.

6.

An adaptive regularization parameter choice strategy for multispectral bioluminescence tomography.

Feng J, Qin C, Jia K, Han D, Liu K, Zhu S, Yang X, Tian J.

Med Phys. 2011 Nov;38(11):5933-44. doi: 10.1118/1.3635221.

PMID:
22047358
8.

Condition Number Regularized Covariance Estimation.

Won JH, Lim J, Kim SJ, Rajaratnam B.

J R Stat Soc Series B Stat Methodol. 2013 Jun 1;75(3):427-450.

9.

Effective Discriminative Feature Selection With Nontrivial Solution.

Tao H, Hou C, Nie F, Jiao Y, Yi D.

IEEE Trans Neural Netw Learn Syst. 2016 Apr;27(4):796-808. doi: 10.1109/TNNLS.2015.2424721. Epub 2015 May 14.

PMID:
25993706
10.

Kronecker-Basis-Representation Based Tensor Sparsity and Its Applications to Tensor Recovery.

Xie Q, Zhao Q, Meng D, Xu Z.

IEEE Trans Pattern Anal Mach Intell. 2017 Aug 2. doi: 10.1109/TPAMI.2017.2734888. [Epub ahead of print]

PMID:
28783623
11.

Alternating direction method for balanced image restoration.

Xie S, Rahardja S.

IEEE Trans Image Process. 2012 Nov;21(11):4557-67. doi: 10.1109/TIP.2012.2206043. Epub 2012 Jun 26.

PMID:
22752137
12.

A Generic Path Algorithm for Regularized Statistical Estimation.

Zhou H, Wu Y.

J Am Stat Assoc. 2014;109(506):686-699.

13.

[Formula: see text]-regularized recursive total least squares based sparse system identification for the error-in-variables.

Lim JS, Pang HS.

Springerplus. 2016 Aug 31;5(1):1460. doi: 10.1186/s40064-016-3120-6. eCollection 2016.

14.

Disease prediction based on functional connectomes using a scalable and spatially-informed support vector machine.

Watanabe T, Kessler D, Scott C, Angstadt M, Sripada C.

Neuroimage. 2014 Aug 1;96:183-202. doi: 10.1016/j.neuroimage.2014.03.067. Epub 2014 Apr 1.

15.

Sparse logistic regression with a L1/2 penalty for gene selection in cancer classification.

Liang Y, Liu C, Luan XZ, Leung KS, Chan TM, Xu ZB, Zhang H.

BMC Bioinformatics. 2013 Jun 19;14:198. doi: 10.1186/1471-2105-14-198.

16.

ACCELERATING CARDIOVASCULAR IMAGING BY EXPLOITING REGIONAL LOW-RANK STRUCTURE VIA GROUP SPARSITY.

Christodoulou AG, Babacan SD, Liang ZP.

Proc IEEE Int Symp Biomed Imaging. 2012 Dec 31;2012:330-333.

17.

The graphical lasso: New insights and alternatives.

Mazumder R, Hastie T.

Electron J Stat. 2012 Nov 9;6:2125-2149.

18.

Homogeneity Pursuit.

Ke T, Fan J, Wu Y.

J Am Stat Assoc. 2015;110(509):175-194.

19.

Nonlocal sparse and low-rank regularization for optical flow estimation.

Dong W, Shi G, Hu X, Ma Y.

IEEE Trans Image Process. 2014 Oct;23(10):4527-38. doi: 10.1109/TIP.2014.2352497. Epub 2014 Aug 27.

PMID:
25167553
20.

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