Abstract: This paper conducts a thorough comparative analysis of optimization algorithms for an unconstrained convex optimization problem. It contrasts traditional methods like Gradient Descent (GD) ...

Join order optimization is among the most crucial query optimization problems, and its central position is also evident in the new research field where quantum computing is applied to database ...

Introduction: We present Quantum Adaptive Search (QAGS), a hybrid quantum-classical algorithm for global optimization of multivariate functions. The method employs an adaptive mechanism that ...

This post was sponsored by Peec AI. The opinions expressed in this article are the sponsor’s own. The first step of any good GEO campaign is creating something that LLM-driven answer machines actually ...

Implementation of numerical optimization algorithms in MATLAB, including derivative-free and gradient-based methods for unconstrained problems, and projection techniques for constrained optimization.

The article debunks the common belief that trial-and-error improvements equate to true optimization. It provides a deep dive into how RTO works—from mathematical ...

ABSTRACT: In this paper, we investigate the convergence of the generalized Bregman alternating direction method of multipliers (ADMM) for solving nonconvex separable problems with linear constraints.

ABSTRACT: The alternating direction method of multipliers (ADMM) and its symmetric version are efficient for minimizing two-block separable problems with linear constraints. However, both ADMM and ...