重访最大权:非凸优化序列求解凸优化
Max-Weight Revisited: Sequences of Non-Convex Optimisations Solving Convex Optimisations
摘要:
我们研究凸优化的最大权方法和对偶次梯度方法之间的联系。我们发现,强连接存在,我们建立了一个干净的,统一的理论框架,包括最大权重和对偶次梯度方法作为特殊情况。我们的分析只使用初等方法,并且在性质上不是渐近的。它还允许我们建立一个明确的和直接的离散队列占用率和拉格朗日乘子之间的联系。
英文摘要:
We investigate the connections between max-weight approaches and dual subgradient methods for convex optimisation. We find that strong connections exist and we establish a clean, unifying theoretical framework that includes both max-weight and dual subgradient approaches as special cases. Our analysis uses only elementary methods, and is not asymptotic in nature. It also allows us to establish an explicit and direct connection between discrete queue occupancies and Lagrange multipliers.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。