The Linearized Bregman Method via Split Feasibility Problems: Analysis and Generalizations

09/09/2013
by   Dirk A. Lorenz, et al.
0

The linearized Bregman method is a method to calculate sparse solutions to systems of linear equations. We formulate this problem as a split feasibility problem, propose an algorithmic framework based on Bregman projections and prove a general convergence result for this framework. Convergence of the linearized Bregman method will be obtained as a special case. Our approach also allows for several generalizations such as other objective functions, incremental iterations, incorporation of non-gaussian noise models or box constraints.

READ FULL TEXT

page 21

page 22

page 23

page 25

research
10/30/2021

Convergence and Semi-convergence of a class of constrained block iterative methods

In this paper, we analyze the convergence projected non-stationary bloc...
research
03/15/2023

A Bregman-Kaczmarz method for nonlinear systems of equations

We propose a new randomized method for solving systems of nonlinear equa...
research
10/22/2020

Planning with Submodular Objective Functions

We study planning with submodular objective functions, where instead of ...
research
01/23/2011

Statistical Multiresolution Dantzig Estimation in Imaging: Fundamental Concepts and Algorithmic Framework

In this paper we are concerned with fully automatic and locally adaptive...
research
10/08/2018

Split-Correctness in Information Extraction

Programs for extracting structured information from text, namely informa...

Please sign up or login with your details

Forgot password? Click here to reset