Regularized Jacobi iteration for decentralized convex quadratic optimization with separable constraints
We consider multi-agent, convex quadratic optimization programs subject to separable constraints, where the constraint function of each agent involves only its local decision vector, while the decision vectors of all agents are coupled via a common objective function. We focus on a regularized varia...
| Hauptverfasser: | , , |
|---|---|
| Format: | Journal article |
| Veröffentlicht: |
IEEE
2018
|