Convex Optimization for Machine Learning, Changho Suh
Автор: Stephen Boyd Название: Convex Optimization ISBN: 0521833787 ISBN-13(EAN): 9780521833783 Издательство: Cambridge Academ Рейтинг: Цена: 17950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The focus of this 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.
Описание: This is the first elementary exposition of the main ideas of complexity theory for convex optimization. Up to now, most of the material can be found only in special journals and research monographs. The book covers optimal methods and lower complexity bounds for smooth and non-smooth convex optimization. A separate chapter is devoted to polynomial-time interior-point methods. Audience: The book is suitable for industrial engineers and economists.
Автор: Bonnans J Frederic Название: Convex and Stochastic Optimization ISBN: 3030149765 ISBN-13(EAN): 9783030149765 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Поставка под заказ.
Описание: This textbook provides an introduction to convex duality for optimization problems in Banach spaces, integration theory, and their application to stochastic programming problems in a static or dynamic setting. It introduces and analyses the main algorithms for stochastic programs, while the theoretical aspects are carefully dealt with.The reader is shown how these tools can be applied to various fields, including approximation theory, semidefinite and second-order cone programming and linear decision rules.This textbook is recommended for students, engineers and researchers who are willing to take a rigorous approach to the mathematics involved in the application of duality theory to optimization with uncertainty.
Автор: Pardalos Panos M., Zilinskas Antanas, Zilinskas Julius Название: Non-Convex Multi-Objective Optimization ISBN: 3319869817 ISBN-13(EAN): 9783319869810 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.
Автор: Zaslavski Alexander J. Название: Convex Optimization with Computational Errors ISBN: 3030378241 ISBN-13(EAN): 9783030378240 Издательство: Springer Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Preface.- 1. Introduction.- 2. Subgradient Projection Algorithm.- 3. The Mirror Descent Algorithm.- 4. Gradient Algorithm with a Smooth Objective Function.- 5. An Extension of the Gradient Algorithm.- 6. Continuous Subgradient Method.- 7. An optimization problems with a composite objective function.- 8. A zero-sum game with two-players.- 9. PDA-based method for convex optimization.- 10 Minimization of quasiconvex functions.-11. Minimization of sharp weakly convex functions.-12. A Projected Subgradient Method for Nonsmooth Problems.- References. -Index.
Автор: Juditsky Anatoli, Nemirovski Arkadi Название: Statistical Inference Via Convex Optimization ISBN: 0691197296 ISBN-13(EAN): 9780691197296 Издательство: Wiley Рейтинг: Цена: 13939.00 р. Наличие на складе: Поставка под заказ.
Описание:
This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences.
Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems--sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals--demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems.
Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.
Автор: Borwein, Jonathan M. Lewis, Adrian S. (university Of Waterloo) Название: Convex analysis and nonlinear optimization ISBN: 1441921273 ISBN-13(EAN): 9781441921277 Издательство: Springer Рейтинг: Цена: 8378.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Optimization is a rich and thriving mathematical discipline, and the underlying theory of current computational optimization techniques grows ever more sophisticated. This new edition adds material on semismooth optimization, as well as several new proofs.
Автор: Panos M. Pardalos; Antanas ?ilinskas; Julius ?ilin Название: Non-Convex Multi-Objective Optimization ISBN: 3319610058 ISBN-13(EAN): 9783319610054 Издательство: Springer Рейтинг: Цена: 12577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Recent results on non-convex multi-objective optimization problems and methods are presented in this book, with particular attention to expensive black-box objective functions.
Автор: Sorin-Mihai Grad Название: Vector Optimization and Monotone Operators via Convex Duality ISBN: 3319088998 ISBN-13(EAN): 9783319088990 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book investigates several duality approaches for vector optimization problems, while also comparing them. Special attention is paid to duality for linear vector optimization problems, for which a vector dual that avoids the shortcomings of the classical ones is proposed.
Автор: Sorin-Mihai Grad Название: Vector Optimization and Monotone Operators via Convex Duality ISBN: 3319361902 ISBN-13(EAN): 9783319361901 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book investigates several duality approaches for vector optimization problems, while also comparing them. Special attention is paid to duality for linear vector optimization problems, for which a vector dual that avoids the shortcomings of the classical ones is proposed.
Автор: Roman G. Strongin; Yaroslav D. Sergeyev Название: Global Optimization with Non-Convex Constraints ISBN: 0792364902 ISBN-13(EAN): 9780792364900 Издательство: Springer Рейтинг: Цена: 43184.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space-filling curves and to economize the search, constraint is accounted separately (penalties are not employed). The multicriteria case is also considered.
Автор: Nicolas Hadjisavvas; Panos M. Pardalos Название: Advances in Convex Analysis and Global Optimization ISBN: 0792369424 ISBN-13(EAN): 9780792369424 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A conference on Convex Analysis and Global Optimization was held in 2000 in Greece in honour of the memory of C. Caratheodory (1873-1950). This volume contains a selection of papers based on talks presented at the conference. The two themes of convexity and global optimization pervade the book.
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