Geometric Science of Information PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Geometric Science of Information PDF full book. Access full book title Geometric Science of Information by Frank Nielsen. Download full books in PDF and EPUB format.
Author: Frank Nielsen
Publisher: Springer
ISBN: 331925040X
Category : Computers
Languages : en
Pages : 788
Get Book Here
Book Description
This book constitutes the refereed proceedings of the Second International Conference on Geometric Science of Information, GSI 2015, held in Palaiseau, France, in October 2015. The 80 full papers presented were carefully reviewed and selected from 110 submissions and are organized into the following thematic sessions: Dimension reduction on Riemannian manifolds; optimal transport; optimal transport and applications in imagery/statistics; shape space and diffeomorphic mappings; random geometry/homology; Hessian information geometry; topological forms and Information; information geometry optimization; information geometry in image analysis; divergence geometry; optimization on manifold; Lie groups and geometric mechanics/thermodynamics; computational information geometry; Lie groups: novel statistical and computational frontiers; geometry of time series and linear dynamical systems; and Bayesian and information geometry for inverse problems.
Author: Frank Nielsen
Publisher: Springer
ISBN: 331925040X
Category : Computers
Languages : en
Pages : 788
Get Book Here
Book Description
This book constitutes the refereed proceedings of the Second International Conference on Geometric Science of Information, GSI 2015, held in Palaiseau, France, in October 2015. The 80 full papers presented were carefully reviewed and selected from 110 submissions and are organized into the following thematic sessions: Dimension reduction on Riemannian manifolds; optimal transport; optimal transport and applications in imagery/statistics; shape space and diffeomorphic mappings; random geometry/homology; Hessian information geometry; topological forms and Information; information geometry optimization; information geometry in image analysis; divergence geometry; optimization on manifold; Lie groups and geometric mechanics/thermodynamics; computational information geometry; Lie groups: novel statistical and computational frontiers; geometry of time series and linear dynamical systems; and Bayesian and information geometry for inverse problems.
Author: Frédéric Barbaresco
Publisher: MDPI
ISBN: 3038424242
Category : Computers
Languages : en
Pages : 473
Get Book Here
Book Description
This book is a printed edition of the Special Issue "Differential Geometrical Theory of Statistics" that was published in Entropy
Author: Charles E.M. Pearce
Publisher: Springer Science & Business Media
ISBN: 0387980962
Category : Mathematics
Languages : en
Pages : 409
Get Book Here
Book Description
The 21 self-contained chapters in this book, include recent developments in several optimization-related topics such as decision theory, linear programming, turnpike theory, duality theory, convex analysis, and queueing theory. This work will be a valuable tool not only to specialists interested in the technical detail and various applications presented, but also to researchers interested in building upon the book’s theoretical results.
Author: American Mathematical Society. Short Course
Publisher: American Mathematical Soc.
ISBN: 082183584X
Category : Mathematics
Languages : en
Pages : 154
Get Book Here
Book Description
This volume presents proceedings from the AMS short course, Trends in Optimization 2004, held at the Joint Mathematics Meetings in Phoenix (AZ). It focuses on seven exciting areas of discrete optimization. In particular, Karen Aardal describes Lovasz's fundamental algorithm for producing a short vector in a lattice by basis reduction and H.W. Lenstra's use of this idea in the early 1980s in his polynomial-time algorithm for integer programming in fixed dimension. Aardal's article, lucid presentations of the material. It also contains practical developments using computational tools. Bernd Sturmfels' article, Algebraic recipes for integer programming, discusses how methods of commutative algebra and algebraic combinatorics can be used successfully to attack integer programming problems. Specifically, Grobner bases play a central role in algorithmic theory and practice. Moreover, it is shown that techniques based on short rational functions are bringing new insights, such as in computing the integer programming gap. Overall, these articles, together with five other contributions, make this volume an impressive compilation on the state-of-the-art of optimization. It is suitable for graduate students and researchers interested in discrete optimization.
Author: Jean-Bernard Lasserre
Publisher: Springer Science & Business Media
ISBN: 0387094148
Category : Business & Economics
Languages : en
Pages : 167
Get Book Here
Book Description
This book analyzes and compares four closely related problems, namely linear programming, integer programming, linear integration, and linear summation (or counting). The book provides some new insights on duality concepts for integer programs.
Author: Yurii Nesterov
Publisher: SIAM
ISBN: 9781611970791
Category : Mathematics
Languages : en
Pages : 414
Get Book Here
Book Description
Specialists working in the areas of optimization, mathematical programming, or control theory will find this book invaluable for studying interior-point methods for linear and quadratic programming, polynomial-time methods for nonlinear convex programming, and efficient computational methods for control problems and variational inequalities. A background in linear algebra and mathematical programming is necessary to understand the book. The detailed proofs and lack of "numerical examples" might suggest that the book is of limited value to the reader interested in the practical aspects of convex optimization, but nothing could be further from the truth. An entire chapter is devoted to potential reduction methods precisely because of their great efficiency in practice.
Author: Stephen P. Boyd
Publisher: Cambridge University Press
ISBN: 9780521833783
Category : Business & Economics
Languages : en
Pages : 744
Get Book Here
Book Description
Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained minimization problems, and interior-point methods. The focus of the book is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance and economics.
Author:
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 1884
Get Book Here
Book Description
Author: Cornelis Roos
Publisher: Springer Science & Business Media
ISBN: 0387263799
Category : Mathematics
Languages : en
Pages : 501
Get Book Here
Book Description
The era of interior point methods (IPMs) was initiated by N. Karmarkar’s 1984 paper, which triggered turbulent research and reshaped almost all areas of optimization theory and computational practice. This book offers comprehensive coverage of IPMs. It details the main results of more than a decade of IPM research. Numerous exercises are provided to aid in understanding the material.
Author: Aharon Ben-Tal
Publisher: SIAM
ISBN: 0898714915
Category : Technology & Engineering
Languages : en
Pages : 500
Get Book Here
Book Description
Here is a book devoted to well-structured and thus efficiently solvable convex optimization problems, with emphasis on conic quadratic and semidefinite programming. The authors present the basic theory underlying these problems as well as their numerous applications in engineering, including synthesis of filters, Lyapunov stability analysis, and structural design. The authors also discuss the complexity issues and provide an overview of the basic theory of state-of-the-art polynomial time interior point methods for linear, conic quadratic, and semidefinite programming. The book's focus on well-structured convex problems in conic form allows for unified theoretical and algorithmical treatment of a wide spectrum of important optimization problems arising in applications.
