A Symmetric Cone Proximal Multiplier Algorithm

A Symmetric Cone Proximal Multiplier Algorithm

© 2023 by IJETT Journal
Volume-71 Issue-1
Year of Publication : 2023
Author : Erik Alex Papa Quiroz, Miguel Angel Cano Lengua, Julio Cesar Lopez Luis, Rolando Ichpas Tapia
DOI : 10.14445/22315381/IJETT-V71I1P223

How to Cite?

Erik Alex Papa Quiroz, Miguel Angel Cano Lengua, Julio Cesar Lopez Luis, Rolando Ichpas Tapia, "A Symmetric Cone Proximal Multiplier Algorithm," International Journal of Engineering Trends and Technology, vol. 71, no. 1, pp. 257-270, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I1P223

This paper introduces a proximal multipliers algorithm to solve separable convex symmetric cone minimization problems subject to linear constraints. The algorithm is motivated by the method proposed by Sarmiento et al. (2016, optimization v.65, 2, 501-537), but we consider in the finite-dimensional vectorial spaces, further to an inner product, a Euclidean Jordan Algebra. Under some natural assumptions on convex analysis, it is demonstrated that all accumulation points of the primal-dual sequences generated by the algorithm are solutions to the problem and assuming strong assumptions on the generalized distances; we obtain the global convergence to a minimize point. To show the algorithm's functionality, we provide an application to find the optimal hyperplane in Support Vector Machine (SVM) for binary classification.

Symmetric convex cone optimization, Separable techniques, Proximal distances, Proximal method of multipliers, Support vector machine.

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