Distributed Averaging in the presence of a Sparse Cut
| dc.creator | Narayanan, Hariharan | |
| dc.date | 2008-03-25 | |
| dc.date | 2008-04-30 | |
| dc.date.accessioned | 2026-07-07T09:35:45Z | |
| dc.date.available | 2026-07-07T09:35:45Z | |
| dc.description | We consider the question of averaging on a graph that has one sparse cut separating two subgraphs that are internally well connected. While there has been a large body of work devoted to algorithms for distributed averaging, nearly all algorithms involve only {\it convex} updates. In this paper, we suggest that {\it non-convex} updates can lead to significant improvements. We do so by exhibiting a decentralized algorithm for graphs with one sparse cut that uses non-convex averages and has an averaging time that can be significantly smaller than the averaging time of known distributed algorithms, such as those of \cite{tsitsiklis, Boyd}. We use stochastic dominance to prove this result in a way that may be of independent interest. | |
| dc.description | 8 pages | |
| dc.identifier | https://arxiv.org/abs/0803.3642 | |
| dc.identifier | http://arxiv.org/abs/0803.3642 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/159937 | |
| dc.subject | Distributed, Parallel, and Cluster Computing | |
| dc.title | Distributed Averaging in the presence of a Sparse Cut | |
| dc.type | text |