Iterative Methods for Optimization
by C.T. Kelley
Publisher: Society for Industrial Mathematics 1987
Number of pages: 188
This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality.
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by P.-A. Absil, R. Mahony, R. Sepulchre - Princeton University Press
Many science and engineering problems can be rephrased as optimization problems on matrix search spaces endowed with a manifold structure. This book shows how to exploit the structure of such problems to develop efficient numerical algorithms.
by Sebastien Bubeck - arXiv.org
This text presents the main complexity theorems in convex optimization and their algorithms. Starting from the fundamental theory of black-box optimization, the material progresses towards recent advances in structural and stochastic optimization.
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This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation. Authors develop a framework in which a Bayesian formulation of the problem provides the bedrock for the derivation and analysis of algorithms.
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This book is intended to both serve as a reference guide and a text for a course on Applied Mathematical Programming. The text concentrates upon conceptual issues, problem formulation, computerized problem solution, and results interpretation.