Optimization on Riemannian manifolds-the result of smooth geometry and optimization
merging into one elegant modern framework-spans many areas of science and engineering …

The theory and applications of Iteration Methods is a very fast-developing field of numerical
analysis and computer methods. The second edition is completely updated and continues to …

This book introduces advanced numerical-functional analysis to beginning computer
science researchers. The reader is assumed to have had basic courses in numerical …

A semi-local analysis of Newton's method for solving nonlinear inclusion problems in
Banach space is presented in this paper. Under an affine majorant condition on the …

In this paper, Smale's α theory is generalized to the context of intrinsic Newton iteration on
geodesically complete analytic Riemannian and Hermitian manifolds. Results are valid for …

This is the first paper dealing with the study of weak sharp minima for constrained
optimization problems on Riemannian manifolds, which are important in many applications …

We describe the first gradient methods on Riemannian manifolds to achieve accelerated
rates in the non-convex case. Under Lipschitz assumptions on the Riemannian gradient and …

We consider variational inequality problems for set-valued vector fields on general
Riemannian manifolds. The existence results of the solution, convexity of the solution set …

Adaptive regularization with cubics (ARC) is an algorithm for unconstrained, non-convex
optimization. Akin to the trust-region method, its iterations can be thought of as approximate …

We establish the existence and uniqueness results for variational inequality problems on
Riemannian manifolds and solve completely the open problem proposed in [SZ Németh …