Abstract The Extreme Learning Machine is a single-hidden-layer feedforward learning
algorithm, which has been successfully applied in regression and classification problems in …

Generative Artificial Intelligence (GAI) has sparked a transformative wave across various
domains, including machine learning, healthcare, business, and entertainment, owing to its …

The alternating direction method of multipliers (ADMM) is an efficient splitting method for
solving separable optimization with linear constraints. In this paper, an inertial proximal …

We propose a general inertial version of the proximal alternating linearized minimization
(PALM)(denoted by NiPALM) for a class of nonconvex and nonsmooth minimization …

This paper investigates the convergence properties and applications of the three-operator
splitting method, also known as the Davis–Yin splitting (DYS) method, integrated with …

Blind deconvolution is a technique to recover an original signal without knowing a
convolving filter. It is naturally formulated as a minimization of a quartic objective function …

In this paper, a class of nonconvex optimization with linearly constrained is considered. An
inertial Bregman generalized alternating direction method of multiplies is investigated for …

In this paper, we propose an inertial proximal splitting method for solving the non-convex
optimization problem, and the new method employs the idea of inertial proximal point to …

We study a novel inertial proximal-gradient method for composite optimization. The
proposed method alternates between a variable metric proximal-gradient iteration with …

Recent research has shown the significant performance of stochastic gradient descent
(SGD) coupled with a momentum trick in solving convex empirical risk minimization (ERM) …