# Two-step inertial Bregman proximal alternating linearized minimization algorithm for nonconvex and nonsmooth problems

arXiv: https://arxiv.org/abs/2306.07614 · HTML: https://mlsanity.com/paper/2306.07614/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2023.

## Built on by (most cited first, 2 of 2)

- [Edge-guided Low-light Image Enhancement with Inertial Bregman Alternating Linearized Minimization](https://mlsanity.com/paper/2403.01142/) (2024)
- [Generalized Geometry Block Proximal Linearized Method for Multiblock Nonconvex and Nonsmooth Optimization](https://mlsanity.com/paper/2609.39301/) (2026)

## Abstract (arXiv)

In this paper, we study an algorithm for solving a class of nonconvex and nonsmooth nonseparable optimization problems. Based on proximal alternating linearized minimization (PALM), we propose a new iterative algorithm which combines two-step inertial extrapolation and Bregman distance. By constructing appropriate benefit function, with the help of Kurdyka--Lojasiewicz property we establish the convergence of the whole sequence generated by proposed algorithm. We apply the algorithm to signal recovery, quadratic fractional programming problem and show the effectiveness of proposed algorithm.