| 分布式有限时间重球法 |
| |
| 作者姓名： | 曲志海 陆疌 |
| |
| 作者单位： | 上海科技大学信息科学与技术学院, 上海 201210;中国科学院上海微系统与信息技术研究所, 上海 200050;中国科学院大学, 北京 100049 |
| |
| 基金项目： | 国家自然科学基金（61603254）资助 |
| |
| 摘 要： | 结合有限时间共识算法及一阶加速算法重球法提出分布式有限时间重球法.本算法的优点为可以保证所有节点在每个周期都达到共识,同时达到与集中式重球法相同阶数的收敛速率.通过数值仿真将该算法与其他分布式优化算法应用于机器学习问题上,展现了该算法的优良性能.
|
| 关 键 词： | 分布式优化 算法设计 有限时间共识算法 重球法 |
| 收稿时间： | 2020-01-06 |
| 修稿时间： | 2020-02-26 |
Distributed finite-time-consensus-based heavy-ball algorithm |
| |
| Authors: | QU Zhihai LU Jie |
| |
| Institution: | School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China;Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China;University of Chinese Academy of Sciences, Beijing 100049, China |
| |
| Abstract: | Based on the finite-time-consensus algorithm and the heavy-ball algorithm which is a first order accelerate algorithm, a distributed optimization algorithm is proposed. The algorithm can achieve consensus after every periodic updates. The non-ergodic convergence rate is at the same order of the centralized heavy-ball algorithm. In addition, the numerical examples compare our algorithm with other state-of-art distributed optimization algorithms on machine learning problems and show the competitive performance. |
| |
| Keywords: | distributed optimization algorithm design finite-time-consensus algorithm heavy-ball algorithm |
|
| 点击此处可从《》浏览原始摘要信息 |
| 点击此处可从《》下载免费的PDF全文 |
|
