Convex Functions And Optimization Methods On Riemannian Manifolds

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Convex Functions and Optimization Methods on Riemannian Manifolds

Author : C. Udriste
Publisher : Springer Science & Business Media
ISBN 13 : 9401583900
Total Pages : 365 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Convex Functions and Optimization Methods on Riemannian Manifolds by : C. Udriste

Download or read book Convex Functions and Optimization Methods on Riemannian Manifolds written by C. Udriste and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 functions and dynamical systems because it is unfortunately "nowhere" to be found in the same context; existing textbooks on convex functions on Euclidean spaces or on dynamical systems do not mention what happens in Riemannian geometry, while the papers dealing with Riemannian manifolds usually avoid discussing elementary facts. Usually a convex function on a Riemannian manifold is a real valued function whose restriction to every geodesic arc is convex.

Convex Functions and Optimization Methods on Riemannian Manifolds

Author : Constantin Udriste
Publisher : Springer
ISBN 13 : 9789401583916
Total Pages : 350 pages
Book Rating : 4.5/5 (839 download)

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Book Synopsis Convex Functions and Optimization Methods on Riemannian Manifolds by : Constantin Udriste

Download or read book Convex Functions and Optimization Methods on Riemannian Manifolds written by Constantin Udriste and published by Springer. This book was released on 2012-12-22 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 functions and dynamical systems because it is unfortunately "nowhere" to be found in the same context; existing textbooks on convex functions on Euclidean spaces or on dynamical systems do not mention what happens in Riemannian geometry, while the papers dealing with Riemannian manifolds usually avoid discussing elementary facts. Usually a convex function on a Riemannian manifold is a real valued function whose restriction to every geodesic arc is convex.

Riemannian Optimization and Its Applications

Author : Hiroyuki Sato
Publisher : Springer Nature
ISBN 13 : 3030623912
Total Pages : 129 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Riemannian Optimization and Its Applications by : Hiroyuki Sato

Download or read book Riemannian Optimization and Its Applications written by Hiroyuki Sato and published by Springer Nature. This book was released on 2021-02-17 with total page 129 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Optimization Algorithms on Matrix Manifolds

Author : P.-A. Absil
Publisher : Princeton University Press
ISBN 13 : 1400830249
Total Pages : 240 pages
Book Rating : 4.4/5 (8 download)

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Book Synopsis Optimization Algorithms on Matrix Manifolds by : P.-A. Absil

Download or read book Optimization Algorithms on Matrix Manifolds written by P.-A. Absil and published by Princeton University Press. This book was released on 2009-04-11 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Handbook of Variational Methods for Nonlinear Geometric Data

Author : Philipp Grohs
Publisher : Springer Nature
ISBN 13 : 3030313514
Total Pages : 703 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Handbook of Variational Methods for Nonlinear Geometric Data by : Philipp Grohs

Download or read book Handbook of Variational Methods for Nonlinear Geometric Data written by Philipp Grohs and published by Springer Nature. This book was released on 2020-04-03 with total page 703 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Beyond Traditional Probabilistic Methods in Economics

Author : Vladik Kreinovich
Publisher : Springer
ISBN 13 : 3030042006
Total Pages : 1167 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Beyond Traditional Probabilistic Methods in Economics by : Vladik Kreinovich

Download or read book Beyond Traditional Probabilistic Methods in Economics written by Vladik Kreinovich and published by Springer. This book was released on 2018-11-24 with total page 1167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent research on probabilistic methods in economics, from machine learning to statistical analysis. Economics is a very important – and at the same a very difficult discipline. It is not easy to predict how an economy will evolve or to identify the measures needed to make an economy prosper. One of the main reasons for this is the high level of uncertainty: different difficult-to-predict events can influence the future economic behavior. To make good predictions and reasonable recommendations, this uncertainty has to be taken into account. In the past, most related research results were based on using traditional techniques from probability and statistics, such as p-value-based hypothesis testing. These techniques led to numerous successful applications, but in the last decades, several examples have emerged showing that these techniques often lead to unreliable and inaccurate predictions. It is therefore necessary to come up with new techniques for processing the corresponding uncertainty that go beyond the traditional probabilistic techniques. This book focuses on such techniques, their economic applications and the remaining challenges, presenting both related theoretical developments and their practical applications.

Mathematics and Computing

Author : Ram N. Mohapatra
Publisher : Springer
ISBN 13 : 8132224523
Total Pages : 500 pages
Book Rating : 4.1/5 (322 download)

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Book Synopsis Mathematics and Computing by : Ram N. Mohapatra

Download or read book Mathematics and Computing written by Ram N. Mohapatra and published by Springer. This book was released on 2015-06-25 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses recent developments and contemporary research in mathematics, statistics and their applications in computing. All contributing authors are eminent academicians, scientists, researchers and scholars in their respective fields, hailing from around the world. This is the second conference on mathematics and computing organized at Haldia Institute of Technology, India. The conference has emerged as a powerful forum, offering researchers a venue to discuss, interact and collaborate, and stimulating the advancement of mathematics and its applications in computer science. The book will allow aspiring researchers to update their knowledge of cryptography, algebra, frame theory, optimizations, stochastic processes, compressive sensing, functional analysis, complex variables, etc. Educating future consumers, users, producers, developers and researchers in mathematics and computing is a challenging task and essential to the development of modern society. Hence, mathematics and its applications in computing are of vital importance to a broad range of communities, including mathematicians and computing professionals across different educational levels and disciplines. In current research, modeling and simulation, making decisions under uncertainty and pattern recognition have become very common. Professionals across different educational levels and disciplines need exposure to advances in mathematics and computing. In this context, this book presents research papers on applicable areas of current interest. It also includes papers in which experts summarize research findings, such as signal processing and analysis and low-rank-matrix approximation for solving large systems, which will emerge as powerful tools for further research. These new advances and cutting-edge research in the fields of mathematics and their applications to computing are of paramount importance for young researchers.

Variational and Monotonicity Methods in Nonsmooth Analysis

Author : Nicuşor Costea
Publisher : Springer Nature
ISBN 13 : 3030816710
Total Pages : 450 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Variational and Monotonicity Methods in Nonsmooth Analysis by : Nicuşor Costea

Download or read book Variational and Monotonicity Methods in Nonsmooth Analysis written by Nicuşor Costea and published by Springer Nature. This book was released on 2021-09-20 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a modern and comprehensive presentation of a wide variety of problems arising in nonlinear analysis, game theory, engineering, mathematical physics and contact mechanics. It includes recent achievements and puts them into the context of the existing literature. The volume is organized in four parts. Part I contains fundamental mathematical results concerning convex and locally Lipschits functions. Together with the Appendices, this foundational part establishes the self-contained character of the text. As the title suggests, in the following sections, both variational and topological methods are developed based on critical and fixed point results for nonsmooth functions. The authors employ these methods to handle the exemplary problems from game theory and engineering that are investigated in Part II, respectively Part III. Part IV is devoted to applications in contact mechanics. The book will be of interest to PhD students and researchers in applied mathematics as well as specialists working in nonsmooth analysis and engineering.

Nonsmooth Optimization and Its Applications

Author : Seyedehsomayeh Hosseini
Publisher : Springer
ISBN 13 : 3030113701
Total Pages : 154 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Nonsmooth Optimization and Its Applications by : Seyedehsomayeh Hosseini

Download or read book Nonsmooth Optimization and Its Applications written by Seyedehsomayeh Hosseini and published by Springer. This book was released on 2019-03-29 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since nonsmooth optimization problems arise in a diverse range of real-world applications, the potential impact of efficient methods for solving such problems is undeniable. Even solving difficult smooth problems sometimes requires the use of nonsmooth optimization methods, in order to either reduce the problem’s scale or simplify its structure. Accordingly, the field of nonsmooth optimization is an important area of mathematical programming that is based on by now classical concepts of variational analysis and generalized derivatives, and has developed a rich and sophisticated set of mathematical tools at the intersection of theory and practice. This volume of ISNM is an outcome of the workshop "Nonsmooth Optimization and its Applications," which was held from May 15 to 19, 2017 at the Hausdorff Center for Mathematics, University of Bonn. The six research articles gathered here focus on recent results that highlight different aspects of nonsmooth and variational analysis, optimization methods, their convergence theory and applications.

Geometry and Statistics

Author :
Publisher : Academic Press
ISBN 13 : 0323913466
Total Pages : 490 pages
Book Rating : 4.3/5 (239 download)

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Book Synopsis Geometry and Statistics by :

Download or read book Geometry and Statistics written by and published by Academic Press. This book was released on 2022-07-15 with total page 490 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geometry and Statistics, Volume 46 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters written by an international board of authors. - Provides the authority and expertise of leading contributors from an international board of authors - Presents the latest release in the Handbook of Statistics series - Updated release includes the latest information on Geometry and Statistics

Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2

Author :
Publisher : Elsevier
ISBN 13 : 0444641416
Total Pages : 706 pages
Book Rating : 4.4/5 (446 download)

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Book Synopsis Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2 by :

Download or read book Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2 written by and published by Elsevier. This book was released on 2019-10-16 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 2, Volume 20, surveys the contemporary developments relating to the analysis and learning of images, shapes and forms, covering mathematical models and quick computational techniques. Chapter cover Alternating Diffusion: A Geometric Approach for Sensor Fusion, Generating Structured TV-based Priors and Associated Primal-dual Methods, Graph-based Optimization Approaches for Machine Learning, Uncertainty Quantification and Networks, Extrinsic Shape Analysis from Boundary Representations, Efficient Numerical Methods for Gradient Flows and Phase-field Models, Recent Advances in Denoising of Manifold-Valued Images, Optimal Registration of Images, Surfaces and Shapes, and much more. - Covers contemporary developments relating to the analysis and learning of images, shapes and forms - Presents mathematical models and quick computational techniques relating to the topic - Provides broad coverage, with sample chapters presenting content on Alternating Diffusion and Generating Structured TV-based Priors and Associated Primal-dual Methods

Lagrangian and Hamiltonian Methods For Nonlinear Control 2006

Author : Francesco Bullo
Publisher : Springer
ISBN 13 : 3540738908
Total Pages : 399 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Lagrangian and Hamiltonian Methods For Nonlinear Control 2006 by : Francesco Bullo

Download or read book Lagrangian and Hamiltonian Methods For Nonlinear Control 2006 written by Francesco Bullo and published by Springer. This book was released on 2007-10-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Lectures on Convex Optimization

Author : Yurii Nesterov
Publisher : Springer
ISBN 13 : 3319915789
Total Pages : 603 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Lectures on Convex Optimization by : Yurii Nesterov

Download or read book Lectures on Convex Optimization written by Yurii Nesterov and published by Springer. This book was released on 2018-11-19 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive, modern introduction to convex optimization, a field that is becoming increasingly important in applied mathematics, economics and finance, engineering, and computer science, notably in data science and machine learning. Written by a leading expert in the field, this book includes recent advances in the algorithmic theory of convex optimization, naturally complementing the existing literature. It contains a unified and rigorous presentation of the acceleration techniques for minimization schemes of first- and second-order. It provides readers with a full treatment of the smoothing technique, which has tremendously extended the abilities of gradient-type methods. Several powerful approaches in structural optimization, including optimization in relative scale and polynomial-time interior-point methods, are also discussed in detail. Researchers in theoretical optimization as well as professionals working on optimization problems will find this book very useful. It presents many successful examples of how to develop very fast specialized minimization algorithms. Based on the author’s lectures, it can naturally serve as the basis for introductory and advanced courses in convex optimization for students in engineering, economics, computer science and mathematics.

An Introduction to Optimization on Smooth Manifolds

Author : Nicolas Boumal
Publisher : Cambridge University Press
ISBN 13 : 1009178717
Total Pages : 358 pages
Book Rating : 4.0/5 (91 download)

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Book Synopsis An Introduction to Optimization on Smooth Manifolds by : Nicolas Boumal

Download or read book An Introduction to Optimization on Smooth Manifolds written by Nicolas Boumal and published by Cambridge University Press. This book was released on 2023-03-16 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Scale Space and Variational Methods in Computer Vision

Author : Alfred M. Bruckstein
Publisher : Springer
ISBN 13 : 3642247857
Total Pages : 811 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Scale Space and Variational Methods in Computer Vision by : Alfred M. Bruckstein

Download or read book Scale Space and Variational Methods in Computer Vision written by Alfred M. Bruckstein and published by Springer. This book was released on 2012-01-03 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-conference proceedings of the Third International Conference on Scale Space Methods and Variational Methods in Computer Vision, SSVM 2011, held in Ein-Gedi, Israel in May/June 2011. The 24 revised full papers presented together with 44 poster papers were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections on denoising and enhancement, segmentation, image representation and invariants, shape analysis, and optical flow.

Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces

Author : Michael Ulbrich
Publisher : SIAM
ISBN 13 : 1611970687
Total Pages : 315 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces by : Michael Ulbrich

Download or read book Semismooth Newton Methods for Variational Inequalities and Constrained Optimization Problems in Function Spaces written by Michael Ulbrich and published by SIAM. This book was released on 2011-07-28 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive treatment of semismooth Newton methods in function spaces: from their foundations to recent progress in the field. This book is appropriate for researchers and practitioners in PDE-constrained optimization, nonlinear optimization and numerical analysis, as well as engineers interested in the current theory and methods for solving variational inequalities.

Matrix Information Geometry

Author : Frank Nielsen
Publisher : Springer Science & Business Media
ISBN 13 : 3642302327
Total Pages : 454 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Matrix Information Geometry by : Frank Nielsen

Download or read book Matrix Information Geometry written by Frank Nielsen and published by Springer Science & Business Media. This book was released on 2012-08-07 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents advances in matrix and tensor data processing in the domain of signal, image and information processing. The theoretical mathematical approaches are discusses in the context of potential applications in sensor and cognitive systems engineering. The topics and application include Information Geometry, Differential Geometry of structured Matrix, Positive Definite Matrix, Covariance Matrix, Sensors (Electromagnetic Fields, Acoustic sensors) and Applications in Cognitive systems, in particular Data Mining.