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

arXiv: https://arxiv.org/abs/1309.2094 · HTML: https://mlsanity.com/paper/1309.2094/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Sep 2013.

## Built on by (most cited first, 3 of 3)

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- [Power of ℓ1-Norm Regularized Kaczmarz Algorithms for High-Order Tensor Recovery](https://mlsanity.com/paper/2405.08275/) (2024)

## Abstract (arXiv)

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.