And finally in Theorem 3.3, we show that the average function [5] of a trigonometrically ρ-convex function is also trigonometrically ρ-convex. 2. Definitions and Preliminary Results. In this section ...

The method of nonlinear conjugate gradients (NCG) is widely used in practice for unconstrained optimization, but it satisfies weak complexity bounds at best when applied to smooth convex functions. In ...

We introduce a property of Banach spaces, called uniform convex-transitivity, which falls between almost transitivity and convex transitivity. We will provide examples of uniformly convex-transitive ...

This chapter helps the students to identify convex functions, convex sets, and convex optimization problems. It presents comparison between a convex and a non‐convex function. The chapter discusses ...

This example is based on Dynamical System Modeling Using Neural ODE and applies convex constraints on both the neural network underpinning the dynamics of the physical system, as well as the ODE ...

Matrix inequalities and convex functions constitute a central theme in modern mathematical analysis, with far‐reaching implications across numerical analysis, optimisation, quantum information ...