An invitation to optimization with Riemannian geometry for applied mathematics, computer science and engineering students and researchers.
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Nicolas Boumal is Assistant Professor of Mathematics at the École Polytechnique Fédérale 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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Da: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condizione: Very Good. Cover and edges may have some wear. Codice articolo mon0003657100
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Da: Marlton Books, Bridgeton, NJ, U.S.A.
Condizione: Acceptable. Readable, but has significant damage / tears. Has a remainder mark. hardcover Used - Acceptable 2023. Codice articolo AB-012060
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: As New. Unread book in perfect condition. Codice articolo 44867854
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Da: California Books, Miami, FL, U.S.A.
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: Rarewaves.com USA, London, LONDO, Regno Unito
Hardback. Condizione: New. 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. Codice articolo LU-9781009166171
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
Hardback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days. Codice articolo C9781009166171
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