Anderson acceleration for iteratively reweighted $\ell_1$ algorithm

arXiv:2403.07271v1 Announce Type: cross
Abstract: Iteratively reweighted L1 (IRL1) algorithm is a common algorithm for solving sparse optimization problems with nonconvex and nonsmooth regularization. The development of its acceleration algorithm, often employing Nesterov acceleration, has sparked significant interest. Nevertheless, the convergence and complexity analysis of these acceleration algorithms consistently poses substantial challenges. Recently, Anderson acceleration has gained prominence owing to its exceptional performance for speeding up fixed-point iteration, with numerous recent studies applying it to gradient-based algorithms. Motivated by the …

abstract algorithm algorithms analysis anderson arxiv challenges complexity convergence cs.ai cs.lg development eess.sp math.oc optimization regularization type