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1588. Local linear convergence of parallel projection algorithms with reduced lifting
Invited abstract in session WB-42: Iterative Methods for Feasibility and Optimization Problems, stream Variational Analysis and Continuous Optimization.
Wednesday, 10:30-12:00Room: 98 (building: 306)
Authors (first author is the speaker)
| 1. | Rubén Campoy
|
| Department of Mathematics, Universidad de Alicante |
Abstract
Different notions on regularity of sets and of collection of sets play an important role in the analysis of the convergence of projection algorithms in nonconvex scenarios. While some projection algorithms can be applied to feasibility problems defined by finitely many sets, some other require the use of a product space reformulation to construct equivalent problems with two sets. In this work we analyze how some regularity properties are preserved under a reformulation in a product space of reduced dimension. This allows us to establish local linear convergence of parallel projection methods which are constructed through this reformulation.
Keywords
- Continuous Optimization
- Parallel Algorithms and Implementation
Status: accepted
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