Back to results

Syracuse University

Implicit Fixed-point Proximity Framework for Optimization Problems and Its Applications

Abstract

dc:description.abstract

<p>A variety of optimization problems especially in the field of image processing are not differentiable in nature. The non-differentiability of the objective functions together with the large dimension of the underlying images makes minimizing the objective function theoretically challenging and numerically difficult. The fixed-point proximity framework that we will systematically study in this dissertation provides a direct and unified methodology for finding solutions to those optimization problems. The framework approaches the models arising from applications straightforwardly by using various fixed point techniques as well as convex analysis tools such as the subdifferential and proximity operator.</p> <p>With the notion of proximity operator, we can convert those optimization problems into finding fixed points of nonlinear operators. Under the fixed-point proximity framework, these fixed point problems are often solved through iterative schemes in which each iteration can be computed in an explicit form. We further explore this fixed point formulation, and develop implicit iterative schemes for finding fixed points of nonlinear operators associated with the underlying problems, with the goal of relaxing restrictions in the development of solving the fixed point equations. Theoretical analysis is provided for the convergence of implicit algorithms proposed under the framework. The numerical experiments on image reconstruction models demonstrate that the proposed implicit fixed-point proximity algorithms work well in comparison with existing explicit fixed-point proximity algorithms in terms of the consumed computational time and accuracy of the solutions.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Mathematics
Year
2018

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Liu, Xiaoxia
Contributors dc:contributor
  • Yuesheng Xu
  • Lixin Shen

Subjects

dc:subject × 5

Identifiers

dc:identifier.*
Repository record dc:identifier
https://surface.syr.edu/etd/897
OAI identifier oai:identifier
oai:surface.syr.edu:etd-1898

Chain of custody

source
Harvested from
Syracuse University
Base URL
surface.syr.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Liu, Xiaoxia. Implicit Fixed-point Proximity Framework for Optimization Problems and Its Applications. Dissertation thesis, 2018. https://surface.syr.edu/etd/897