# Delay-agnostic Asynchronous Coordinate Update Algorithm

arXiv: https://arxiv.org/abs/2305.08535 · HTML: https://mlsanity.com/paper/2305.08535/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 15 May 2023.

## Built on by (most cited first, 4 of 4)

- [Asynchronous SGD on Graphs: a Unified Framework for Asynchronous Decentralized and Federated Optimization](https://mlsanity.com/paper/2311.00465/) (2023)
- [A survey on secure decentralized optimization and learning](https://mlsanity.com/paper/2408.08628/) (2024)
- [Asynchronous Distributed Optimization with Delay-free Parameters](https://mlsanity.com/paper/2312.06508/) (2023)
- [Scalable Asynchronous Federated Modeling for Spatial Data](https://mlsanity.com/paper/2510.01771/) (2025)

## Abstract (arXiv)

We propose a delay-agnostic asynchronous coordinate update algorithm (DEGAS) for computing operator fixed points, with applications to asynchronous optimization. DEGAS includes novel asynchronous variants of ADMM and block-coordinate descent as special cases. We prove that DEGAS converges under both bounded and unbounded delays under delay-free parameter conditions. We also validate by theory and experiments that DEGAS adapts well to the actual delays. The effectiveness of DEGAS is demonstrated by numerical experiments on classification problems.