Distributed Online Optimization in Dynamic Environments Using Mirror Descent
This work addresses decentralized online optimization in nonstationary environments. A network of agents aim to track the minimizer of a global, time-varying, and convex function. The minimizer follows a known linear dynamics corrupted by unknown unstructured noise. At each time, the global function...
| Main Author: | |
|---|---|
| Other Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE),
2018-09-11T19:40:25Z.
|
| Subjects: | |
| Online Access: | Get fulltext |