Name
Abstract | ||
|---|---|---|
This paper considers the distributed optimization of a sum of locally observable, nonconvex functions. The optimization is performed over a multiagent networked system, and each local function depends only on a subset of the variables. An asynchronous and distributed alternating directions method of multipliers (ADMM) method that allows the nodes to defer or skip the computation and transmission o... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/TSIPN.2016.2593896 | IEEE Transactions on Signal and Information Processing over Networks |
Keywords | DocType | Volume |
Algorithm design and analysis,Distributed algorithms,Convergence,Multi-agent systems,Optimization,Cost function | Journal | 3 |
Issue | ISSN | Citations |
1 | 2373-776X | 4 |
PageRank | References | Authors |
0.45 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sandeep Kumar | 1 | 7 | 1.51 |
| Rahul Jain | 2 | 784 | 71.51 |
| Ketan Rajawat | 3 | 124 | 25.44 |