Now showing items 1-5 of 5
On the Convergence of an Active Set Method for L1 Minimization
We analyze an abridged version of the active-set algorithm FPC_AS for solving the L1-regularized least squares problem. The active set algorithm alternatively iterates between two stages. In the first "nonmonotone line ...
The Total Variation Regularized L1 Model for Multiscale Decomposition
This paper studies the total variation regularization model with an L1 fidelity term (TV-L1) for decomposing an image into features of different scales. We first show that the images produced by this model can be formed ...
Alternating Direction Augmented Lagrangian Methods for Semidefinite Programming
We present an alternating direction method based on an augmented Lagrangian framework for solving semidefinite programming (SDP) problems in standard form. At each iteration, the algorithm, also known as a two-splitting ...
A Curvilinear Search Method for p-Harmonic Flows on Spheres
The problem of finding p-harmonic flows arises in a wide range of applications including micromagnetics, liquid crystal theory, directional diffusion, and chromaticity denoising. In this paper, we propose an innovative ...
A Comparison of Three Total Variation Based Texture Extraction Models
This paper qualitatively compares three recently proposed models for signal/image texture extraction based on total variation minimization:the Meyer, Vese-Osher, and TV-L1 models. We formulate discrete versions of these ...