Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Optimization Algorithms on Matrix Manifolds
Top Free Data Science Books 🌠 - 100% Free or Open Source!
  • Title Optimization Algorithms on Matrix Manifolds
  • Authors P.-A. Absil, R. Mahony, R. Sepulchre
  • Publisher: Princeton University Press; illustrated edition edition (December 3, 2008)
  • Paperback: 240 pages
  • Language: English
  • ISBN-10: 0691132984
  • ISBN-13: 978-0691132983
  • Share This:  

Book Description

This book 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.

The treatment strikes an appropriate balance between mathematical, numerical, and algorithmic points of view. The quality of the writing is quite high and very readable. The topic is very timely and is certainly of interest to myself and my students."--Kyle A. Gallivan, Florida State University

About the Authors
  • P.-A. Absil is associate professor of mathematical engineering at the Universite Catholique de Louvain in Belgium.
Reviews and Rating: Related Book Categories: Read and Download Links: Similar Books:
  • Manifolds - Current Research Areas (Paul Bracken)

    This book cover a number of subjects which will be of interest to workers in these areas. It is hoped that the papers here will be able to provide a useful resource for researchers with regard to current fields of research in this important area.

  • Fundamentals of Matrix Algebra (Gregory Hartman)

    A college (or advanced high school) level text dealing with the basic principles of matrix and linear algebra. It covers solving systems of linear equations, matrix arithmetic, the determinant, eigenvalues, and linear transformations.

  • Convex Optimization for Machine Learning (Changho Suh)

    This book covers an introduction to convex optimization, one of the powerful and tractable optimization problems that can be efficiently solved on a computer. The goal is to help develop a sense of what convex optimization is, and how it can be used.

  • Introduction to Online Convex Optimization (Elad Hazan)

    This book presents a robust machine learning approach that contains elements of mathematical optimization, game theory, and learning theory: an optimization method that learns from experience as more aspects of the problem are observed.

  • Convex Optimization (Stephen Boyd, et al.)

    On recognizing convex optimization problems and then finding the most appropriate technique for solving them. It contains many worked examples in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

  • Optimization for Decision Making: Linear and Quadratic Models

    This book illustrates how to formulate real world problems using linear and quadratic models; It focus on developing modeling skills to support valid decision making for complex real world problems.

  • Global Optimization Algorithms - Theory and Application

    This book is devoted to global optimization algorithms, which are methods to find optimal solutions for given problems. It especially focuses on Evolutionary Computation by discussing evolutionary algorithms, genetic algorithms, Genetic Programming, etc.

  • Inventory Analytics: A Practicable, Python-Driven Approach

    This book provides a comprehensive and accessible introduction to the theory and practice of Inventory Control - a significant research area central to supply chain planning. It adopts a practicable, Python-driven approach to illustrating theories and concepts.

  • Algorithms for Decision Making (Mykel Kochenderfer, et al)

    This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them.

Book Categories
:
Other Categories
Resources and Links