Opening book details…
Can I read Convex functions and optimization methods on Riemannian manifolds on EtoBox?
Convex functions and optimization methods on Riemannian manifolds by Udriște, Constantin is a nonfiction available to read on EtoBox.
What is Convex functions and optimization methods on Riemannian manifolds about?
The object of this book is to present the basic facts of convex functions, standard dynamical systems, descent numerical algorithms and some computer programs on Riemannian manifolds in a form suitable for applied mathematicians, scientists and engineers. It contains mathematical information on these subjects and applications distributed in seven chapters whose topics are close to my own areas of research: Metric properties of Riemannian manifolds, First and second variations of the p-energy of a curve; Convex functions on Riemannian manifolds; Geometric examples of convex functions; Flows, convexity and energies; Semidefinite Hessians and applications; Minimization of functions on Riemannian manifolds. All the numerical algorithms, computer programs and the appendices (Riemannian convexity of functions f:R ~ R, Descent methods on the Poincare plane, Descent methods on the sphere, Completeness and convexity on Finsler manifolds) constitute an attempt to make accesible to all users of this book some basic computational techniques and implementation of geometric structures. To further aid the readers,this book also contains a part of the folklore about Riemannian geometry, convex fun
Who reads Convex functions and optimization methods on Riemannian manifolds?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Udriște, Constantin
- Publisher
- Springer; Kluwer Academic
- Published
- 2013
- Language
- EN
- ISBN
- 9780792330028
- Category
- nonfiction
- Subjects
- Mathematics, Stem
Other editions & translations
More by Udriște, Constantin
Browse all works by Udriște, Constantin
Similar books
- Optimization Algorithms on Matrix Manifolds — Absil, P.-A., Mahony, R., Sepulchre, Rodolphe (2007)
- Convex Optimization in Normed Spaces: Theory, Methods and Examples (SpringerBriefs in Optimization Book 0) — Juan Peypouquet (2015)
- Convex and Stochastic Optimization (Universitext) — J. Frédéric Bonnans J. (2019)
- Lectures on Modern Convex Optimization — Ben-Tal A., Nemirovski A. (2023)
- Non-Convex Multi-Objective Optimization — Panos M. Pardalos, Antanas Žilinskas and Julius (2017)
- Convex Optimization Algorithms — Bertsekas D.P. (2015)