An Introduction to Optimization on Smooth Manifolds - Softcover

Boumal, Nicolas

9781009166157: An Introduction to Optimization on Smooth Manifolds

Softcover

ISBN 10: 1009166158 ISBN 13: 9781009166157

Verlag: Cambridge University Press, 2023

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An invitation to optimization with Riemannian geometry for applied mathematics, computer science and engineering students and researchers.

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�ber die Autorin bzw. den Autor

Nicolas Boumal is Assistant Professor of Mathematics at the �cole Polytechnique F�d�rale de Lausanne (EPFL) in Switzerland, and an Associate Editor of the journal Mathematical Programming. His current research focuses on optimization, statistical estimation and numerical analysis. Over the course of his career, Boumal has contributed to several modern theoretical advances in Riemannian optimization. He is a lead-developer of the award-winning toolbox Manopt, which facilitates experimentation with optimization on manifolds.

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Verlag: Cambridge University Press
Erscheinungsdatum: 2023
Sprache: Englisch
ISBN 10: 1009166158
ISBN 13: 9781009166157
Einband: Taschenbuch
Anzahl der Seiten: 358
Kontakt zum Hersteller: Nicht verf�gbar
Verantwortliche Person: Avery
https://www.avery.fr/

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Optimization on Riemannian manifolds-the...

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An Introduction to Optimization on Smooth Manifolds

Nicolas Boumal

Verlag: Cambridge University Press, 2023

ISBN 10: 1009166158 ISBN 13: 9781009166157

Gebraucht Paperback

Anbieter: World of Books (was SecondSale), Montgomery, IL, USA

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Paperback. Zustand: Very Good. Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help students and researchers in applied mathematics, computer science and engineering gain a firm mathematical grounding to use these tools confidently in their research. Its charts-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book. Artikel-Nr. CIN1009166158VG

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