A novel fixed-point based two-step inertial algorithm for convex minimization in deep learning data classification

A novel fixed-point based two-step inertial algorithm for convex minimization in deep learning data classification

In this paper, we present a novel two-step inertial algorithm for finding a common fixed-point of a countable family of nonexpansive mappings. Under mild assumptions, we prove a weak convergence theorem for the method. We then demonstrate its versatility by applying it to convex minimization problem...

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Bibliographic Details
Main Authors: Kobkoon Janngam, Suthep Suantai, Rattanakorn Wattanataweekul
Format: Article
Language:English
Published: AIMS Press 2025-03-01
Series:AIMS Mathematics
Subjects:
convex minimization problem
data classification
deep learning
fixed-point
optimization
two-step inertial algorithm
Online Access:https://www.aimspress.com/article/doi/10.3934/math.2025283
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