# Exact solution to the random sequential dynamics of a message passing algorithm

arXiv: https://arxiv.org/abs/2101.01571 · HTML: https://mlsanity.com/paper/2101.01571/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 22 references that are in the map.
- First posted on arXiv 5 Jan 2021.

## Builds on (most cited first, 1 of 1)

- [Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification](https://mlsanity.com/paper/2006.06098/) (2020)

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

- [Analysis of Random Sequential Message Passing Algorithms for Approximate Inference](https://mlsanity.com/paper/2202.08198/) (2022)
- [A Convergence Analysis of Approximate Message Passing with Non-Separable Functions and Applications to Multi-Class Classification](https://mlsanity.com/paper/2402.08676/) (2024)

## Abstract (arXiv)

We analyze the random sequential dynamics of a message passing algorithm for Ising models with random interactions in the large system limit. We derive exact results for the two-time correlation functions and the speed of convergence. The em de Almedia-Thouless stability criterion of the static problem is found to be necessary and sufficient for the global convergence of the random sequential dynamics.