| Title:
|
A stochastic mirror-descent algorithm for solving $AXB=C$ over an multi-agent system (English) |
| Author:
|
Wang, Yinghui |
| Author:
|
Cheng, Songsong |
| Language:
|
English |
| Journal:
|
Kybernetika |
| ISSN:
|
0023-5954 (print) |
| ISSN:
|
1805-949X (online) |
| Volume:
|
57 |
| Issue:
|
2 |
| Year:
|
2021 |
| Pages:
|
256-271 |
| Summary lang:
|
English |
| . |
| Category:
|
math |
| . |
| Summary:
|
In this paper, we consider a distributed stochastic computation of $AXB=C$ with local set constraints over an multi-agent system, where each agent over the network only knows a few rows or columns of matrixes. Through formulating an equivalent distributed optimization problem for seeking least-squares solutions of $AXB=C$, we propose a distributed stochastic mirror-descent algorithm for solving the equivalent distributed problem. Then, we provide the sublinear convergence of the proposed algorithm. Moreover, a numerical example is also given to illustrate the effectiveness of the proposed algorithm. (English) |
| Keyword:
|
distributed computation of matrix equation |
| Keyword:
|
multi-agent system |
| Keyword:
|
sublinear convergence |
| Keyword:
|
stochastic mirror descent algorithm |
| MSC:
|
68M15 |
| MSC:
|
93A14 |
| idZBL:
|
Zbl 07396266 |
| idMR:
|
MR4273575 |
| DOI:
|
10.14736/kyb-2021-2-0256 |
| . |
| Date available:
|
2021-07-30T13:06:38Z |
| Last updated:
|
2021-11-01 |
| Stable URL:
|
http://hdl.handle.net/10338.dmlcz/149038 |
| . |
| Reference:
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| . |
