512. Proximal Algorithms for a class of abstract convex functions
Invited abstract in session MB-9: Generalized convexity and monotonicity 1, stream Generalized convexity and monotonicity.
Monday, 10:30-12:30Room: B100/8013
Authors (first author is the speaker)
| 1. | The Hung Tran
|
| Optimization and Modeling of Dynamical System, System Research Institute |
Abstract
In this paper, we analyze a class of nonconvex optimization problems from the viewpoint of abstract convexity. Using the respective generalizations of the subgradient, we propose an abstract notion of a proximal operator and derive several algorithms, namely abstract proximal point method, abstract forward-backward method, and abstract projected subgradient method. Global convergence results for all algorithms are discussed, and numerical examples are given.
Keywords
- Global optimization
- Computational mathematical optimization
- Non-smooth optimization
Status: accepted
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