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Stochastic Optimization for Large-Scale Machine Learning, Chauhan Vinod Kumar


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Цена: 24499.00р.
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Автор: Chauhan Vinod Kumar
Название:  Stochastic Optimization for Large-Scale Machine Learning
ISBN: 9781032131757
Издательство: Taylor&Francis
Классификация:


ISBN-10: 1032131756
Обложка/Формат: Hardcover
Страницы: 158
Вес: 0.53 кг.
Дата издания: 19.11.2021
Язык: English
Иллюстрации: 4 tables, black and white; 25 line drawings, black and white; 25 illustrations, black and white
Размер: 25.40 x 17.78 x 1.12 cm
Читательская аудитория: Postgraduate, research & scholarly
Ссылка на Издательство: Link
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Поставляется из: Европейский союз
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 and Its Applications with Fuzzy Adaptive Simulated Annealing

Автор: Hime Aguiar e Oliveira Junior; Lester Ingber; Anto
Название: Stochastic Global Optimization and Its Applications with Fuzzy Adaptive Simulated Annealing
ISBN: 364243343X ISBN-13(EAN): 9783642433436
Издательство: Springer
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Цена: 18284.00 р.
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Описание: With applications to many areas in science and technology, the technique examined in this volume is a highly effective algorithmic problem-solving tool. Contributions from leading experts cover the latest research and provide detailed examples of its use.

Stochastic Optimization Methods

Автор: Kurt Marti
Название: Stochastic Optimization Methods
ISBN: 3642098363 ISBN-13(EAN): 9783642098369
Издательство: Springer
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Цена: 16769.00 р.
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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.

Bandit Algorithms

Автор: Tor Lattimore, Csaba Szepesvari
Название: Bandit Algorithms
ISBN: 1108486827 ISBN-13(EAN): 9781108486828
Издательство: Cambridge Academ
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Цена: 6970.00 р.
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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.

Stochastic optimization methods

Автор: Marti, Kurt
Название: Stochastic optimization methods
ISBN: 3662500124 ISBN-13(EAN): 9783662500125
Издательство: Springer
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Цена: 18167.00 р.
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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.

Optimization of Stochastic Discrete Systems and Control on Complex Networks

Автор: Dmitrii Lozovanu; Stefan Pickl
Название: Optimization of Stochastic Discrete Systems and Control on Complex Networks
ISBN: 3319358731 ISBN-13(EAN): 9783319358734
Издательство: Springer
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Цена: 18167.00 р.
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Описание: Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems.

Stochastic Learning and Optimization

Автор: Xi-Ren Cao
Название: Stochastic Learning and Optimization
ISBN: 144194222X ISBN-13(EAN): 9781441942227
Издательство: Springer
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Цена: 25853.00 р.
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Описание: Performance optimization is vital in the design and operation of modern engineering systems. This book provides a unified framework based on a sensitivity point of view. It introduces new approaches and proposes new research topics.

Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search

Автор: David L. Woodruff
Название: Advances in Computational and Stochastic Optimization, Logic Programming, and Heuristic Search
ISBN: 1441950230 ISBN-13(EAN): 9781441950239
Издательство: Springer
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Цена: 29209.00 р.
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Описание: Computer Science and Operations Research continue to have a synergistic relationship and this book - as a part of the Operations Research and Computer Science Interface Series - sits squarely in the center of the confluence of these two technical research communities.

Large Scale Linear and Integer Optimization: A Unified Approach

Автор: Richard Kipp Martin
Название: Large Scale Linear and Integer Optimization: A Unified Approach
ISBN: 1461372585 ISBN-13(EAN): 9781461372585
Издательство: Springer
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Цена: 69876.00 р.
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Описание: This is a textbook about linear and integer linear optimization. The major goal of the book is to develop the theory of linear and integer linear optimization in a unified manner and then demonstrate how to use this theory in a modern computing environment to solve very large real world problems.

Large Scale Optimization in Supply Chains and Smart Manufacturing

Автор: Jes?s M. Vel?squez-Berm?dez; Marzieh Khakifirooz;
Название: Large Scale Optimization in Supply Chains and Smart Manufacturing
ISBN: 3030227871 ISBN-13(EAN): 9783030227876
Издательство: Springer
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Цена: 11878.00 р.
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Описание: In this book, theory of large scale optimization is introduced with case studies of real-world problems and applications of structured mathematical modeling. The large scale optimization methods are represented by various theories such as Benders’ decomposition, logic-based Benders’ decomposition, Lagrangian relaxation, Dantzig –Wolfe decomposition, multi-tree decomposition, Van Roy’ cross decomposition and parallel decomposition for mathematical programs such as mixed integer nonlinear programming and stochastic programming. Case studies of large scale optimization in supply chain management, smart manufacturing, and Industry 4.0 are investigated with efficient implementation for real-time solutions. The features of case studies cover a wide range of fields including the Internet of things, advanced transportation systems, energy management, supply chain networks, service systems, operations management, risk management, and financial and sales management. Instructors, graduate students, researchers, and practitioners, would benefit from this book finding the applicability of large scale optimization in asynchronous parallel optimization, real-time distributed network, and optimizing the knowledge-based expert system for convex and non-convex problems.

Hybrid L1 Adaptive Control: Applications of Fuzzy Modeling, Stochastic Optimization and Metaheuristics

Автор: Maiti Roshni, Das Sharma Kaushik, Sarkar Gautam
Название: Hybrid L1 Adaptive Control: Applications of Fuzzy Modeling, Stochastic Optimization and Metaheuristics
ISBN: 3030971015 ISBN-13(EAN): 9783030971014
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book details the designing of hybrid control strategies for practical systems containing time varying uncertainties, disturbances, nonlinearities, unknown parameters, unmodelled dynamics, delays, etc., concurrently. In this book, the advantages of different controllers will be brought together to produce superior control performance for the practical systems. Being aware of the advantages of adaptive controller to tackle unknown constant, time varying uncertainties and time varying disturbances, a variant of adaptive controller, namely L1 adaptive controller, is hybridized with other strategies. In this book, to facilitate optimal parameter setting of the basic L1 adaptive controller, stochastic optimization technique will be hybridized with it. The stability of the optimization technique along with the controller will be guaranteed analytically with the help of spectral radius convergence. The proposed method exhibits satisfactory exploration and exploitation capabilities. Again, this book will throw light on tackling nonlinearities along with uncertainties and disturbances by hybridizing fuzzy logic with L1 adaptive controller. The performances of the designed controllers will be compared with different control methodologies to validate their effectiveness. The overall stability of the nonlinear system with the designed controller will be guaranteed with the help of fuzzy Lyapunov function to retain the zonal behaviour of the system. This fuzzy PDC-L1 adaptive controller is efficient to tackle nonlinearities and at the same time cancels unknown constant, time varying uncertainties and time varying disturbances adequately. This book will also contain four simulation case studies to validate fruitfulness of the designed controllers. To demonstrate the superior control ability of these controllers in tackling practical system, three experimental case studies will also be provided.

Machine Learning, Optimization, and Big Data

Автор: Pardalos
Название: Machine Learning, Optimization, and Big Data
ISBN: 3319514687 ISBN-13(EAN): 9783319514680
Издательство: Springer
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Цена: 9224.00 р.
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Описание: This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD 2016, held in Volterra, Italy, in August 2016. The 40 papers presented in this volume were carefully reviewed and selected from 97 submissions.

Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition

Автор: Serkan Kiranyaz; Turker Ince; Moncef Gabbouj
Название: Multidimensional Particle Swarm Optimization for Machine Learning and Pattern Recognition
ISBN: 3642437621 ISBN-13(EAN): 9783642437625
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book explores multidimensional particle swarm optimization, a technique developed by the authors and presented in a well-defined algorithmic approach. All featured applications are supported with fully documented source code as well as sample datasets.


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