# Chebyshev Inertial Iteration for Accelerating Fixed-Point Iterations

arXiv: https://arxiv.org/abs/2001.03280 · HTML: https://mlsanity.com/paper/2001.03280/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jan 2020.

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

- [Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detection](https://mlsanity.com/paper/2302.04461/) (2023)
- [Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding](https://mlsanity.com/paper/2402.15125/) (2024)

## Abstract (arXiv)

A novel method which is called the Chebyshev inertial iteration for accelerating the convergence speed of fixed-point iterations is presented. The Chebyshev inertial iteration can be regarded as a valiant of the successive over relaxation or Krasnosel'skivi-Mann iteration utilizing the inverse of roots of a Chebyshev polynomial as iteration dependent inertial factors. One of the most notable features of the proposed method is that it can be applied to nonlinear fixed-point iterations in addition to linear fixed-point iterations. Linearization around the fixed point is the key for the analysis on the local convergence rate of the proposed method. The proposed method appears effective in particular for accelerating the proximal gradient methods such as ISTA. It is also proved that the proposed method can successfully accelerate almost any fixed-point iterations if all the eigenvalues of the Jacobian at the fixed point are real.