Can I read A Cyclic Coordinate Descent Algorithm for lq Regularization on EtoBox?

A Cyclic Coordinate Descent Algorithm for lq Regularization by Zeng, Jinshan; Peng, Zhimin; Lin, Shaobo; Xu, Zongben is a scholarly article available to read on EtoBox.

What is A Cyclic Coordinate Descent Algorithm for lq Regularization about?

In recent studies on sparse modeling, $l_q$ ($0<q<1$) regularization has received considerable attention due to its superiorities on sparsity-inducing and bias reduction over the $l_1$ regularization.In this paper, we propose a cyclic coordinate descent (CCD) algorithm for $l_q$ regularization. Our main result states that the CCD algorithm converges globally to a stationary point as long as the stepsize is less than a positive constant. Furthermore, we demonstrate that the CCD algorithm converges to a local minimizer under certain additional conditions. Our numerical experiments demonstrate the efficiency of the CCD algorithm.

Author

Zeng, Jinshan; Peng, Zhimin; Lin, Shaobo; Xu, Zongben

Published

2014

Language

EN