Optimization Algorithms on Matrix Manifolds

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Release : 2009-04-11
Genre : Mathematics
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Book Rating : 249/5 ( reviews)

Optimization Algorithms on Matrix Manifolds - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimization Algorithms on Matrix Manifolds write by P.-A. Absil. This book was released on 2009-04-11. Optimization Algorithms on Matrix Manifolds available in PDF, EPUB and Kindle. Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms. It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction--illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development. In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis. It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists.

Optimization Algorithms on Matrix Manifolds

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Release : 2007-12-23
Genre : Mathematics
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Book Rating : 983/5 ( reviews)

Optimization Algorithms on Matrix Manifolds - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Optimization Algorithms on Matrix Manifolds write by P.-A. Absil. This book was released on 2007-12-23. Optimization Algorithms on Matrix Manifolds available in PDF, EPUB and Kindle. Many problems in the sciences and engineering can be rephrased as optimization problems on matrix search spaces endowed with a so-called manifold structure. This book shows how to exploit the special structure of such problems to develop efficient numerical algorithms. It places careful emphasis on both the numerical formulation of the algorithm and its differential geometric abstraction--illustrating how good algorithms draw equally from the insights of differential geometry, optimization, and numerical analysis. Two more theoretical chapters provide readers with the background in differential geometry necessary to algorithmic development. In the other chapters, several well-known optimization methods such as steepest descent and conjugate gradients are generalized to abstract manifolds. The book provides a generic development of each of these methods, building upon the material of the geometric chapters. It then guides readers through the calculations that turn these geometrically formulated methods into concrete numerical algorithms. The state-of-the-art algorithms given as examples are competitive with the best existing algorithms for a selection of eigenspace problems in numerical linear algebra. Optimization Algorithms on Matrix Manifolds offers techniques with broad applications in linear algebra, signal processing, data mining, computer vision, and statistical analysis. It can serve as a graduate-level textbook and will be of interest to applied mathematicians, engineers, and computer scientists.

Riemannian Optimization and Its Applications

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Release : 2021-02-17
Genre : Technology & Engineering
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Book Rating : 912/5 ( reviews)

Riemannian Optimization and Its Applications - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Riemannian Optimization and Its Applications write by Hiroyuki Sato. This book was released on 2021-02-17. Riemannian Optimization and Its Applications available in PDF, EPUB and Kindle. This brief describes the basics of Riemannian optimization—optimization on Riemannian manifolds—introduces algorithms for Riemannian optimization problems, discusses the theoretical properties of these algorithms, and suggests possible applications of Riemannian optimization to problems in other fields. To provide the reader with a smooth introduction to Riemannian optimization, brief reviews of mathematical optimization in Euclidean spaces and Riemannian geometry are included. Riemannian optimization is then introduced by merging these concepts. In particular, the Euclidean and Riemannian conjugate gradient methods are discussed in detail. A brief review of recent developments in Riemannian optimization is also provided. Riemannian optimization methods are applicable to many problems in various fields. This brief discusses some important applications including the eigenvalue and singular value decompositions in numerical linear algebra, optimal model reduction in control engineering, and canonical correlation analysis in statistics.

Handbook of Variational Methods for Nonlinear Geometric Data

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Release : 2020-04-03
Genre : Mathematics
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Book Rating : 514/5 ( reviews)

Handbook of Variational Methods for Nonlinear Geometric Data - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Handbook of Variational Methods for Nonlinear Geometric Data write by Philipp Grohs. This book was released on 2020-04-03. Handbook of Variational Methods for Nonlinear Geometric Data available in PDF, EPUB and Kindle. This book covers different, current research directions in the context of variational methods for non-linear geometric data. Each chapter is authored by leading experts in the respective discipline and provides an introduction, an overview and a description of the current state of the art. Non-linear geometric data arises in various applications in science and engineering. Examples of nonlinear data spaces are diverse and include, for instance, nonlinear spaces of matrices, spaces of curves, shapes as well as manifolds of probability measures. Applications can be found in biology, medicine, product engineering, geography and computer vision for instance. Variational methods on the other hand have evolved to being amongst the most powerful tools for applied mathematics. They involve techniques from various branches of mathematics such as statistics, modeling, optimization, numerical mathematics and analysis. The vast majority of research on variational methods, however, is focused on data in linear spaces. Variational methods for non-linear data is currently an emerging research topic. As a result, and since such methods involve various branches of mathematics, there is a plethora of different, recent approaches dealing with different aspects of variational methods for nonlinear geometric data. Research results are rather scattered and appear in journals of different mathematical communities. The main purpose of the book is to account for that by providing, for the first time, a comprehensive collection of different research directions and existing approaches in this context. It is organized in a way that leading researchers from the different fields provide an introductory overview of recent research directions in their respective discipline. As such, the book is a unique reference work for both newcomers in the field of variational methods for non-linear geometric data, as well as for established experts that aim at to exploit new research directions or collaborations. Chapter 9 of this book is available open access under a CC BY 4.0 license at link.springer.com.

Introduction to Smooth Manifolds

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Release : 2013-03-09
Genre : Mathematics
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Book Rating : 525/5 ( reviews)

Introduction to Smooth Manifolds - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Introduction to Smooth Manifolds write by John M. Lee. This book was released on 2013-03-09. Introduction to Smooth Manifolds available in PDF, EPUB and Kindle. Author has written several excellent Springer books.; This book is a sequel to Introduction to Topological Manifolds; Careful and illuminating explanations, excellent diagrams and exemplary motivation; Includes short preliminary sections before each section explaining what is ahead and why