A Refined Inertial DC Algorithm for DC Programming
| Autor: | Yu You, Yi-Shuai Niu |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Control and Optimization Optimization and Control (math.OC) Computer Vision and Pattern Recognition (cs.CV) Mechanical Engineering FOS: Mathematics Computer Science - Computer Vision and Pattern Recognition 90C26 90C30 68U10 Aerospace Engineering Electrical and Electronic Engineering Mathematics - Optimization and Control Software Civil and Structural Engineering |
| Popis: | In this paper we consider the difference-of-convex (DC) programming problems, whose objective function is the difference of two convex functions. The classical DC Algorithm (DCA) is well-known for solving this kind of problems, which generally returns a critical point. Recently, an inertial DC algorithm (InDCA) equipped with heavy-ball inertial-force procedure was proposed in de Oliveira et al. (Set-Valued and Variational Analysis 27(4):895--919, 2019), which potentially helps to improve both the convergence speed and the solution quality. Based on InDCA, we propose a refined inertial DC algorithm (RInDCA) equipped with enlarged inertial step-size compared with InDCA. Empirically, larger step-size accelerates the convergence. We demonstrate the subsequential convergence of our refined version to a critical point. In addition, by assuming the Kurdyka-{\L}ojasiewicz (KL) property of the objective function, we establish the sequential convergence of RInDCA. Numerical simulations on checking copositivity of matrices and image denoising problem show the benefit of larger step-size. Comment: 24 pages, 4 figures |
| Databáze: | OpenAIRE |
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