國立高雄大學圖資館 |

登入

回首頁

Stochastic approximationa dynamical systems viewpoint /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Stochastic approximationby Vivek S. Borkar.
其他題名:	a dynamical systems viewpoint /
作者:	Borkar, Vivek S.
出版者:	Singapore :Springer Nature Singapore :2023.
面頁冊數:	xv, 273 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Stochastic approximation.
電子資源:	https://doi.org/10.1007/978-981-99-8277-6
ISBN:	9789819982776$q(electronic bk.)

Stochastic approximationa dynamical systems viewpoint /
Borkar, Vivek S.

Stochastic approximationa dynamical systems viewpoint /[electronic resource] :by Vivek S. Borkar. - Second edition. - Singapore :Springer Nature Singapore :2023. - xv, 273 p. :ill., digital ;24 cm. - Texts and readings in mathematics,v. 482366-8725 ;. - Texts and readings in mathematics ;74..

1. Introduction -- 2. Convergence Analysis -- 3. Finite Time Bounds and Traps -- 4. Stability Criteria -- 5. Stochastic Recursive Inclusions -- 6. Asynchronous Schemes -- 7. A Limit Theorem for Fluctuations -- 8. Multiple Timescales -- 9. Constant Stepsize Algorithms -- 10. General Noise Models -- 11. Stochastic Gradient Schemes -- 12. Liapunov and Related Systems -- 13. Appendix A: Topics in Analysis -- 14. Appendix B: Ordinary Differential Equations -- 15. Appendix C: Topics in Probability -- Bibliography -- Index.

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.

ISBN: 9789819982776$q(electronic bk.)

Standard No.: 10.1007/978-981-99-8277-6doiSubjects--Topical Terms:

191094
Stochastic approximation.

LC Class. No.: QA274.2

Dewey Class. No.: 519.2

Stochastic approximationa dynamical systems viewpoint /
LDR:02393nmm a2200349 a 4500 001 654857
003 DE-He213
005 20240131080823.0
006 m d
007 cr nn 008maaau
008 240524s2023 si s 0 eng d
020 $a 9789819982776$q(electronic bk.)
020 $a 9789819982769$q(paper)
024 7 $a 10.1007/978-981-99-8277-6 $2 doi
035 $a 978-981-99-8277-6
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274.2
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.2 $2 23
090 $a QA274.2 $b .B734 2023
100 1 $a Borkar, Vivek S. $3 561477
245 1 0 $a Stochastic approximation $h [electronic resource] : $b a dynamical systems viewpoint / $c by Vivek S. Borkar.
250 $a Second edition.
260 $a Singapore : $b Springer Nature Singapore : $b Imprint: Springer, $c 2023.
300 $a xv, 273 p. : $b ill., digital ; $c 24 cm.
490 1 $a Texts and readings in mathematics, $x 2366-8725 ; $v v. 48
505 0 $a 1. Introduction -- 2. Convergence Analysis -- 3. Finite Time Bounds and Traps -- 4. Stability Criteria -- 5. Stochastic Recursive Inclusions -- 6. Asynchronous Schemes -- 7. A Limit Theorem for Fluctuations -- 8. Multiple Timescales -- 9. Constant Stepsize Algorithms -- 10. General Noise Models -- 11. Stochastic Gradient Schemes -- 12. Liapunov and Related Systems -- 13. Appendix A: Topics in Analysis -- 14. Appendix B: Ordinary Differential Equations -- 15. Appendix C: Topics in Probability -- Bibliography -- Index.
520 $a 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.
650 0 $a Stochastic approximation. $3 191094
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Probability Theory. $3 913371
650 2 4 $a Operations Research and Decision Theory. $3 914898
650 2 4 $a Game Theory. $3 737094
650 2 4 $a Control and Systems Theory. $3 825946
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Texts and readings in mathematics ; $v 74. $3 789679
856 4 0 $u https://doi.org/10.1007/978-981-99-8277-6
950 $a Mathematics and Statistics (SpringerNature-11649)