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 ...

Convex optimization Abstract: 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 ...

Specify tanh activation functions for the non-convex evolution of the 'state' variable (using the NonConvexActivation name-value argument). For more information, see AI Verification: Convex. Create a ...

The main result proved in this paper is that the ratio of the square of a nonnegative convex function to a strictly positive concave function is convex over a convex domain. Some particular cases of ...

Convex optimisation constitutes a fundamental area in applied mathematics where the objective is to identify the minimum of a convex function subject to a set of convex constraints. This framework ...

About A Julia/C++ implementation and numerical examples of adjoint subgradient evaluation for convex ODE relaxations, as described by Zhang and Khan (2024).

ABSTRACT: The aim of this paper is to prove that the average function of a trigonometrically ρ-convex function is trigonometrically ρ-convex. Furthermore, we show the existence of support curves ...

Jensen gave a lower bound to Eρ (T), where ρ is a convex function of the random vector T. Madansky has obtained an upper bound via the theory of moment spaces of multivariate distributions. In ...