Effects of network topology on the performance of consensus and distributed learning of SVMs using ADMM
The Alternating Direction Method of Multipliers (ADMM) is a popular and promising distributed framework for solving large-scale machine learning problems. We consider decentralized consensus-based ADMM in which nodes may only communicate with one-hop neighbors. This may cause slow convergence. We in...
| Үндсэн зохиолчид: | , |
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| Формат: | Өгүүллэг |
| Хэл сонгох: | English |
| Хэвлэсэн: |
PeerJ Inc.
2021-03-01
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| Цуврал: | PeerJ Computer Science |
| Нөхцлүүд: | |
| Онлайн хандалт: | https://peerj.com/articles/cs-397.pdf |