# Optimization in Open Networks via Dual Averaging

arXiv: https://arxiv.org/abs/2105.13348 · HTML: https://mlsanity.com/paper/2105.13348/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 36 references that are in the map.
- First posted on arXiv 27 May 2021.

## Builds on (most cited first, 13 of 13)

- [Asynchronous Decentralized Parallel Stochastic Gradient Descent](https://mlsanity.com/paper/1710.06952/) (2017)
- [Network Topology and Communication-Computation Tradeoffs in Decentralized Optimization](https://mlsanity.com/paper/1709.08765/) (2017)
- [Distributed Online Optimization in Dynamic Environments Using Mirror Descent](https://mlsanity.com/paper/1609.02845/) (2016)
- [Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism](https://mlsanity.com/paper/2012.11579/) (2020)
- [Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions](https://mlsanity.com/paper/1606.02421/) (2016)
- [Optimization and Learning with Information Streams: Time-varying Algorithms and Applications](https://mlsanity.com/paper/1910.08123/) (2019)
- [On the O(1/k) Convergence of Asynchronous Distributed Alternating Direction Method of Multipliers](https://mlsanity.com/paper/1307.8254/) (2013)
- [Asynchronous Distributed Optimization using a Randomized Alternating Direction Method of Multipliers](https://mlsanity.com/paper/1303.2837/) (2013)
- [Stability of Decentralized Gradient Descent in Open Multi-Agent Systems](https://mlsanity.com/paper/2009.05445/) (2020)
- [Time-Varying Convex Optimization via Time-Varying Averaged Operators](https://mlsanity.com/paper/1704.07338/) (2017)
- [Stability of Open Multi-Agent Systems and Applications to Dynamic Consensus](https://mlsanity.com/paper/1906.00890/) (2019)
- [Lower bound performances for average consensus in open multi-agent systems (extended version)](https://mlsanity.com/paper/1909.02475/) (2019)
- [Fundamental Performance Limitations for Average Consensus in Open Multi-Agent Systems](https://mlsanity.com/paper/2004.06533/) (2020)

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

- [Optimization and Learning in Open Multi-Agent Systems](https://mlsanity.com/paper/2501.16847/) (2025)
- [On the Stability Analysis of Open Federated Learning Systems](https://mlsanity.com/paper/2209.12307/) (2022)

## Abstract (arXiv)

In networks of autonomous agents (e.g., fleets of vehicles, scattered sensors), the problem of minimizing the sum of the agents' local functions has received a lot of interest. We tackle here this distributed optimization problem in the case of open networks when agents can join and leave the network at any time. Leveraging recent online optimization techniques, we propose and analyze the convergence of a decentralized asynchronous optimization method for open networks.