Minimization of a smooth function on a sphere or, more generally, on a smooth manifold, is
the simplest non-convex optimization problem. It has a lot of applications. Our goal is to …

The gradient method for minimizing a differentiable convex function on Riemannian
manifolds with lower bounded sectional curvature is analyzed in this paper. An analysis of …

This article is devoted to studying the problem of multiobjective semi-infinite programming
on Hadamard manifolds. We first establish both Karush–Kuhn–Tucker necessary and …

We extend and analyze the trust region method for solving smooth and unconstrained
multicriteria optimization problems on Riemannian manifolds. At each iteration of this …

ABSTRACT A class of polyhedral-spherical configurations as finite point configurations
inscribed into a hypersphere is defined. Approaches to determination of configuration …

Proximal bundle methods are among the most successful approaches for convex and
nonconvex optimization problems in linear spaces and it is natural to extend these methods …

The subgradient method for convex optimization problems on complete Riemannian
manifolds with lower bounded sectional curvature is analysed in this paper. Iteration …

This paper investigates the reduced attitude formation control problem for a group of rigid-
body agents using feedback based on relative attitude information. Under both undirected …

In this paper, we deal with the semivectorial bilevel problem in the Riemannian setting. The
upper level is a scalar optimization problem to be solved by the leader, and the lower level is …

Tools from optimal transport (OT) theory have recently been used to define a notion of
quantile function for directional data. In practice, regularization is mandatory for applications …