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First-Order and Stochastic Optimization Methods for Machine Learning, Lan Guanghui


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Цена: 111790.00T
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Автор: Lan Guanghui
Название:  First-Order and Stochastic Optimization Methods for Machine Learning
ISBN: 9783030395674
Издательство: Springer
Классификация:

ISBN-10: 3030395677
Обложка/Формат: Hardcover
Страницы: 582
Вес: 1.01 кг.
Дата издания: 16.05.2020
Серия: Springer series in the data sciences
Язык: English
Издание: 1st ed. 2020
Иллюстрации: 12 tables, color; 16 illustrations, color; 2 illustrations, black and white; xiii, 582 p. 18 illus., 16 illus. in color.
Размер: 23.39 x 15.60 x 3.33 cm
Читательская аудитория: Professional & vocational
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.

Stochastic Differential Equations

Автор: Oksendal
Название: Stochastic Differential Equations
ISBN: 3540047581 ISBN-13(EAN): 9783540047582
Издательство: Springer
Рейтинг:
Цена: 54820.00 T
Наличие на складе: Есть
Описание: Gives an introduction to the basic theory of stochastic calculus and its applications. This book offers examples in order to motivate and illustrate the theory and show its importance for many applications in for example economics, biology and physics.

Global Optimization Methods in Geophysical Inversion

Автор: Sen
Название: Global Optimization Methods in Geophysical Inversion
ISBN: 1107011906 ISBN-13(EAN): 9781107011908
Издательство: Cambridge Academ
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Цена: 96830.00 T
Наличие на складе: Есть
Описание: This up-to-date new edition provides an overview of global optimization methods, and includes succinct descriptions of background theory, advanced concepts and examples of geophysical inversion, enabling readers to formulate their own applications. A valuable resource for researchers, graduate students and professionals in geophysics, inverse theory, exploration geoscience and engineering.

Bandit Algorithms

Автор: Tor Lattimore, Csaba Szepesvari
Название: Bandit Algorithms
ISBN: 1108486827 ISBN-13(EAN): 9781108486828
Издательство: Cambridge Academ
Рейтинг:
Цена: 46470.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision-making in the face of uncertainty is a challenge in machine learning, and the multi-armed bandit model is a common framework to address it. This comprehensive introduction is an excellent reference for established researchers and a resource for graduate students interested in exploring stochastic, adversarial and Bayesian frameworks.

First-Order and Stochastic Optimization Methods for Machine Learning

Автор: Lan Guanghui
Название: First-Order and Stochastic Optimization Methods for Machine Learning
ISBN: 3030395707 ISBN-13(EAN): 9783030395704
Издательство: Springer
Цена: 130430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book covers not only foundational materials but also the most recent progresses made during the past few years on the area of machine learning algorithms.

Optimization Under Stochastic Uncertainty: Methods, Control and Random Search Methods

Автор: Marti Kurt
Название: Optimization Under Stochastic Uncertainty: Methods, Control and Random Search Methods
ISBN: 3030556611 ISBN-13(EAN): 9783030556617
Издательство: Springer
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Optimal Control under Stochastic Uncertainty.- 2. Stochastic Optimization of Regulators.- 3. Optimal Open-Loop Control of Dynamic Systems under Stochastic Uncertainty.- 4. Construction of feedback control by means of homotopy methods.- 5. Constructions of Limit State Functions.- 6. Random Search Procedures for Global Optimization.- 7. Controlled Random Search under Uncertainty.- 8. Controlled Random Search Procedures for Global Optimization.- 9. Mathematical Model of Random Search Methods and Elementary Properties.- 10. Special Random Search Methods.- 11. Accessibility Theorems.- 12. Convergence Theorems.- 13. Convergence of Stationary Random Search Methods for Positive Success Probability.- 14. Random Search Methods of convergence order U(n-").- 15. Random Search Methods with a Linear Rate of Convergence.- 16. Success/Failure-driven Random Direction Procedures.- 17. Hybrid Methods.- 18. Solving optimization problems under stochastic uncertainty by Random Search Methods(RSM).

Stochastic Optimization for Large-Scale Machine Learning

Автор: Chauhan Vinod Kumar
Название: Stochastic Optimization for Large-Scale Machine Learning
ISBN: 1032131756 ISBN-13(EAN): 9781032131757
Издательство: Taylor&Francis
Рейтинг:
Цена: 163330.00 T
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Описание: Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge. Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods.

Stochastic Global Optimization Methods And Applications To Chemical, Biochemical, Pharmaceutical And Environmental Processes

Автор: Venkateswarlu, Ch.
Название: Stochastic Global Optimization Methods And Applications To Chemical, Biochemical, Pharmaceutical And Environmental Processes
ISBN: 0128173920 ISBN-13(EAN): 9780128173923
Издательство: Elsevier Science
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Цена: 158330.00 T
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Описание:

Stochastic global optimization methods and applications to chemical, biochemical, pharmaceutical and environmental processes presents various algorithms that include the genetic algorithm, simulated annealing, differential evolution, ant colony optimization, tabu search, particle swarm optimization, artificial bee colony optimization, and cuckoo search algorithm. The design and analysis of these algorithms is studied by applying them to solve various base case and complex optimization problems concerning chemical, biochemical, pharmaceutical, and environmental engineering processes.

Design and implementation of various classical and advanced optimization strategies to solve a wide variety of optimization problems makes this book beneficial to graduate students, researchers, and practicing engineers working in multiple domains. This book mainly focuses on stochastic, evolutionary, and artificial intelligence optimization algorithms with a special emphasis on their design, analysis, and implementation to solve complex optimization problems and includes a number of real applications concerning chemical, biochemical, pharmaceutical, and environmental engineering processes.


Stochastic optimization methods

Автор: Marti, Kurt
Название: Stochastic optimization methods
ISBN: 3662500124 ISBN-13(EAN): 9783662500125
Издательство: Springer
Рейтинг:
Цена: 121110.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Stochastic Optimization Methods.- Optimal Control Under Stochastic Uncertainty.- Stochastic Optimal Open-Loop Feedback Control.- Adaptive Optimal Stochastic Trajectory Planning and Control (AOSTPC).- Optimal Design of Regulators.- Expected Total Cost Minimum Design of Plane Frames.- Stochastic Structural Optimization with Quadratic Loss Functions.- Maximum Entropy Techniques.

Designing Engineering Structures using Stochastic Optimization Methods

Название: Designing Engineering Structures using Stochastic Optimization Methods
ISBN: 0367255197 ISBN-13(EAN): 9780367255190
Издательство: Taylor&Francis
Рейтинг:
Цена: 163330.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book reviews mechanical engineering design optimization using stochastic methods. It introduces students and design engineers to practical aspects of complicated mathematical optimization procedures, and outlines steps for wide range of selected engineering design problems.

Optimization Under Stochastic Uncertainty: Methods, Control and Random Search Methods

Автор: Marti Kurt
Название: Optimization Under Stochastic Uncertainty: Methods, Control and Random Search Methods
ISBN: 3030556646 ISBN-13(EAN): 9783030556648
Издательство: Springer
Рейтинг:
Цена: 74530.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 1. Optimal Control under Stochastic Uncertainty.- 2. Stochastic Optimization of Regulators.- 3. Optimal Open-Loop Control of Dynamic Systems under Stochastic Uncertainty.- 4. Construction of feedback control by means of homotopy methods.- 5. Constructions of Limit State Functions.- 6. Random Search Procedures for Global Optimization.- 7. Controlled Random Search under Uncertainty.- 8. Controlled Random Search Procedures for Global Optimization.- 9. Mathematical Model of Random Search Methods and Elementary Properties.- 10. Special Random Search Methods.- 11. Accessibility Theorems.- 12. Convergence Theorems.- 13. Convergence of Stationary Random Search Methods for Positive Success Probability.- 14. Random Search Methods of convergence order U(n-").- 15. Random Search Methods with a Linear Rate of Convergence.- 16. Success/Failure-driven Random Direction Procedures.- 17. Hybrid Methods.- 18. Solving optimization problems under stochastic uncertainty by Random Search Methods(RSM).

Stochastic Optimization Methods in Finance and Energy

Автор: Marida Bertocchi; Giorgio Consigli; Michael A. H.
Название: Stochastic Optimization Methods in Finance and Energy
ISBN: 1461430275 ISBN-13(EAN): 9781461430278
Издательство: Springer
Рейтинг:
Цена: 204040.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents contributions dedicated to applied problems in the financial and energy sectors that have been formulated and solved in a stochastic optimization framework. Coverage also extends to theoretical and computational issues.

Stochastic Optimization Methods

Автор: Kurt Marti
Название: Stochastic Optimization Methods
ISBN: 3642098363 ISBN-13(EAN): 9783642098369
Издательство: Springer
Рейтинг:
Цена: 111790.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Optimization problems arising in practice involve random model parameters. This book features many illustrations, several examples, and applications to concrete problems from engineering and operations research.


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