Abstract: In order to address unconstrained optimization problems, conjugate gradient methods are frequently employed. When considering the unconstrained optimization issue, the accelerated conjugate ...

ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...

In this study, we focus on investigating a nonsmooth convex optimization problem involving the l 1-norm under a non-negative constraint, with the goal of developing an inverse-problem solver for image ...

Want your business to show up in Google’s AI-driven results? The same principles that help you rank in Google Search still matter – but AI introduces new dimensions of context, reputation, and ...

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 ...

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I've read the documentation and to me it looks like features like glass substituion (semi-automatic optimization for chromatism) and a fast (but inaccurate) optimizer (akin to the "Orthogonal Descent ...

Algorithm design and scientific discovery often demand a meticulous cycle of exploration, hypothesis testing, refinement, and validation. Traditionally, these processes rely heavily on expert ...

ABSTRACT: In this paper, we consider a more general bi-level optimization problem, where the inner objective function is consisted of three convex functions, involving a smooth and two non-smooth ...