
doi: 10.1007/bf00938545
handle: 10203/2063
\textit{B. T. Polyak} [USSR Comput. Math. Math. Phys. 9 (1969), No.3, 14-29 (1971; Zbl 0229.65056)] has suggested an improved subgradient method and provided a lower bound on the improvement of the Euclidean distance to an optimal solution. In this paper, we provide a stronger lower bound and show that the direction of movement in this method forms a more acute angle with the direction toward the set of optimal solutions than that in the subgradient method.
Optimization, nondifferentiable optimization, Numerical methods based on nonlinear programming, Nonlinear programming, cutting plane methods, subgradient methods, stronger lower bound, subgradient method
Optimization, nondifferentiable optimization, Numerical methods based on nonlinear programming, Nonlinear programming, cutting plane methods, subgradient methods, stronger lower bound, subgradient method
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 4 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
