Dynamic stochastic optimization

Craig Wilson; Venugopal Veeravalli; Angelia Nedic

doi:10.1109/CDC.2014.7039377

Dynamic stochastic optimization

Craig Wilson, Venugopal Veeravalli, Angelia Nedic

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A framework for sequentially solving stochastic optimization problems with stochastic gradient descent is introduced. Two tracking criteria are considered, one based on being accurate with respect to the mean trajectory and the other based on being accurate in high probability (IHP). An off-line optimization problem is solved to find the constant step size and number of iterations to achieve the desired tracking accuracy. Simulations are used to confirm that this approach provides the desired tracking accuracy.

Original language	English (US)
Title of host publication	53rd IEEE Conference on Decision and Control,CDC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	173-178
Number of pages	6
Edition	February
ISBN (Electronic)	9781479977468
DOIs	https://doi.org/10.1109/CDC.2014.7039377
State	Published - 2014
Event	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014 - Los Angeles, United States Duration: Dec 15 2014 → Dec 17 2014

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Number	February
Volume	2015-February
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Other

Other	2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014
Country/Territory	United States
City	Los Angeles
Period	12/15/14 → 12/17/14

Keywords

adaptive optimization
gradient methods
stochastic optimization

ASJC Scopus subject areas

Control and Systems Engineering
Modeling and Simulation
Control and Optimization

Online availability

10.1109/CDC.2014.7039377

Library availability

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Wilson, C., Veeravalli, V., & Nedic, A. (2014). Dynamic stochastic optimization. In 53rd IEEE Conference on Decision and Control,CDC 2014 (February ed., pp. 173-178). Article 7039377 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, No. February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2014.7039377

Dynamic stochastic optimization. / Wilson, Craig; Veeravalli, Venugopal; Nedic, Angelia.
53rd IEEE Conference on Decision and Control,CDC 2014. February. ed. Institute of Electrical and Electronics Engineers Inc., 2014. p. 173-178 7039377 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2015-February, No. February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Wilson, C, Veeravalli, V & Nedic, A 2014, Dynamic stochastic optimization. in 53rd IEEE Conference on Decision and Control,CDC 2014. February edn, 7039377, Proceedings of the IEEE Conference on Decision and Control, no. February, vol. 2015-February, Institute of Electrical and Electronics Engineers Inc., pp. 173-178, 2014 53rd IEEE Annual Conference on Decision and Control, CDC 2014, Los Angeles, United States, 12/15/14. https://doi.org/10.1109/CDC.2014.7039377

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Dynamic stochastic optimization

Abstract

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Keywords

ASJC Scopus subject areas

Online availability

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