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Sinopsis
This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.
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Acerca del autor
Vivek Shripad Borkar is Professor at the Department of Electrical Engineering, Indian Institute of Technology (IIT) Bombay, Powai, Mumbai, India. Earlier, he held positions at the TIFR Centre for Applicable Mathematics and Indian Institute of Science in Bengaluru; Indian Institute of Science, Bengaluru; Tata Institute of Fundamental Research and Indian Institute of Technology Bombay in Mumbai. He also held visiting positions at the Massachusetts Institute of Technology (MIT), the University of Maryland at College Park, the University of California at Berkeley, and the University of Illinois at Urbana-Champaign, USA.
Professor Borkar obtained his B.Tech. (Electrical Engineering) from the IIT Bombay in 1976, MS (Systems and Control Engineering) from Case Western Reserve University in 1977, and Ph.D. (Electrical Engineering and Computer Sciences) from the University of California, Berkeley, USA, in 1980. He is Fellow of American Mathematical Society, IEEE, and the World Academy of Sciences, and of various science and engineering academies in India. He has won several awards and honours in India and was an invited speaker at the ICM 2006 in Madrid. He has authored/co-authored six books and several archival publications. His primary research interests are in stochastic optimization and control, covering theory and algorithms.
De la contraportada
This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.
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Stochastic Approximation: A Dynamical Systems Viewpoint
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a comprehensive view of the ODE-based approach for the analysis of stochastic approximation algorithmsDiscusses important themes on stability tests, concentration bounds, and avoidance of trapsCovers very recent developments with c. Nº de ref. del artículo: 1171875375
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Stochastic Approximation: A Dynamical Systems Viewpoint
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ISBN 13: 9789819982769
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field. 292 pp. Englisch. Nº de ref. del artículo: 9789819982769
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Stochastic Approximation: A Dynamical Systems Viewpoint
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ISBN 10: 9819982766
ISBN 13: 9789819982769
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field. Nº de ref. del artículo: 9789819982769
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Stochastic Approximation: A Dynamical Systems Viewpoint (Texts and Readings in Mathematics, 48)
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Stochastic Approximation: A Dynamical Systems Viewpoint (Texts and Readings in Mathematics, 48)
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Stochastic Approximation: A Dynamical Systems Viewpoint
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ISBN 10: 9819982766
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Buch. Condición: Neu. Neuware -This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 292 pp. Englisch. Nº de ref. del artículo: 9789819982769
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Stochastic Approximation: A Dynamical Systems Viewpoint (Texts and Readings in Mathematics, 48)
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