1623. Primal-Dual Algorithms for Saddle Point Problems—Convergence Analysis and Equilibrium Properties
Invited abstract in session MC-35: Nonlinear Optimization Algorithms and Applications: 2, stream Continuous and mixed-integer nonlinear programming: theory and algorithms.
Monday, 12:30-14:00Room: Michael Sadler LG15
Authors (first author is the speaker)
| 1. | Deren Han
|
| School of mathematical science, Beihang university |
Abstract
The saddle point problem is a significant class of issues in the fields of optimization and game theory, where both theoretical and applied research have consistently garnered widespread attention. Among the core algorithms to address this problem are those based on primal-dual methods. This report presents a convergence analysis for some fundamental saddle point problems and introduces a novel algorithm that considers the equilibrium between primal and dual aspects.
Keywords
- Algorithms
- Continuous Optimization
- Complexity and Approximation
Status: accepted
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