EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
1460. Dynamic distributed gradient method for strongly monotone variational inequality problem over the common fixed-point constraints
Invited abstract in session WB-43: Recent advances on Variational Inequalities and Equilibrium Problems I, stream Variational Inequalities and Equilibrium Problems: From Theoretical Advances to Real World Applications.
Wednesday, 10:30-12:00Room: 99 (building: 306)
Authors (first author is the speaker)
| 1. | Narin Petrot
|
| Mathematics, Naresuan University |
Abstract
In this talk, we introduce a dynamic distributed conjugate gradient method designed to solve the strongly monotone variational inequality problem across the fixed-point sets intersection of firmly nonexpansive operators. Our method enables the independent computation of a firmly nonexpansive operator alongside a dynamically updated weight at each iteration. This approach aims to enhance the convergence rate of the algorithm by adjusting control factors for each iterative step. By imposing suitable control conditions on relevant parameters, we establish the strong convergence of the iterates towards the unique solution of the variational inequality problem under consideration. Additionally, we conduct numerical experiments and analyze key observations by applying this model to address image classification challenges using support vector machine learning techniques.
Keywords
- Algorithms
- Continuous Optimization
- Convex Optimization
Status: accepted
Back to the list of papers