论文标题
分布式近端分裂算法的速率和加速度
Distributed Proximal Splitting Algorithms with Rates and Acceleration
论文作者
论文摘要
我们分析了一些非常适合大规模凸非平滑优化的通用近端分裂算法。我们使用不同的步骤来得出有关函数值次优或距离的新速率以及新的加速版本，并使用不同的步骤来得出sublinear和线性收敛的结果。此外，我们提出了这些算法的分布式变体，也可以加速。虽然大多数现有结果都是奇异的，但我们的非连接结果显着扩大了我们对原始二偶优化算法的理解。
We analyze several generic proximal splitting algorithms well suited for large-scale convex nonsmooth optimization. We derive sublinear and linear convergence results with new rates on the function value suboptimality or distance to the solution, as well as new accelerated versions, using varying stepsizes. In addition, we propose distributed variants of these algorithms, which can be accelerated as well. While most existing results are ergodic, our nonergodic results significantly broaden our understanding of primal-dual optimization algorithms.
