Modified gradient method for minimization of nonsmooth penalty functions

1994 ◽  
Vol 71 (5) ◽  
pp. 2712-2715
Author(s):  
Yu. M. Danilin ◽  
D. Numazarov

Automatica ◽  
1995 ◽  
Vol 31 (1) ◽  
pp. 115-124 ◽  
Author(s):  
Stefen Hui ◽  
Walter E. Lillo ◽  
Stanislaw H. Żak




Biometrika ◽  
2020 ◽  
Vol 107 (2) ◽  
pp. 397-414 ◽  
Author(s):  
David E Tyler ◽  
Mengxi Yi

Summary The properties of penalized sample covariance matrices depend on the choice of the penalty function. In this paper, we introduce a class of nonsmooth penalty functions for the sample covariance matrix and demonstrate how their use results in a grouping of the estimated eigenvalues. We refer to the proposed method as lassoing eigenvalues, or the elasso.



2000 ◽  
Vol 33 (16) ◽  
pp. 287-291
Author(s):  
Lyudmila N. Polyakova


Cybernetics ◽  
1989 ◽  
Vol 24 (4) ◽  
pp. 511-524
Author(s):  
Yu. M. Danilin


2007 ◽  
Vol 2 (2) ◽  
pp. 39-50
Author(s):  
Vanda Pomezanski
Keyword(s):  


Sign in / Sign up

Export Citation Format

Share Document