Modified gradient method for minimization of nonsmooth penalty functions

1994 ◽  
Vol 71 (5) ◽  
pp. 2712-2715
Author(s):  
Yu. M. Danilin ◽  
D. Numazarov
Keyword(s):  
Gradient Method ◽  
Penalty Functions ◽  
Nonsmooth Penalty

Solving minimum norm problems using penalty functions and the gradient method

Automatica ◽  
1995 ◽  
Vol 31 (1) ◽  
pp. 115-124 ◽  
Author(s):  
Stefen Hui ◽  
Walter E. Lillo ◽  
Stanislaw H. Żak
Keyword(s):  
Gradient Method ◽  
Penalty Functions ◽  
Minimum Norm ◽  
Minimum Norm Problems

Lassoing eigenvalues

Biometrika ◽  
2020 ◽  
Vol 107 (2) ◽  
pp. 397-414 ◽  
Author(s):  
David E Tyler ◽  
Mengxi Yi
Keyword(s):  
Covariance Matrix ◽  
Penalty Function ◽  
Covariance Matrices ◽  
Penalty Functions ◽  
Sample Covariance Matrix ◽  
Sample Covariance Matrices ◽  
Sample Covariance ◽  
Nonsmooth Penalty

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.

Nonsmooth Penalty Functions

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

Corner contact penalty functions in plane and in space

2007 ◽  
Vol 2 (2) ◽  
pp. 39-50
Author(s):  
Vanda Pomezanski
Keyword(s):  
Penalty Functions
Sign in / Sign up

Export Citation Format

Share Document