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Inexact SA Method for Constrained Stochastic Convex SDP and Application in Chinese Stock Market
Joint Authors
Chen, Shuang
Pang, Li-Ping
Lv, Jian
Xia, Zun-quan
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-01-23
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
We propose stochastic convex semidefinite programs (SCSDPs) to handle uncertain data in applications.
For these models, we design an efficient inexact stochastic approximation (SA) method and prove the convergence, complexity, and robust treatment of the algorithm.
We apply the inexact method for solving SCSDPs where the subproblem in each iteration is only solved approximately and show that it enjoys the similar iteration complexity as the exact counterpart if the subproblems are progressively solved to sufficient accuracy.
Numerical experiments show that the method we proposed was effective for uncertain problem.
American Psychological Association (APA)
Chen, Shuang& Pang, Li-Ping& Lv, Jian& Xia, Zun-quan. 2018. Inexact SA Method for Constrained Stochastic Convex SDP and Application in Chinese Stock Market. Journal of Function Spaces،Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1186367
Modern Language Association (MLA)
Chen, Shuang…[et al.]. Inexact SA Method for Constrained Stochastic Convex SDP and Application in Chinese Stock Market. Journal of Function Spaces No. 2018 (2018), pp.1-12.
https://search.emarefa.net/detail/BIM-1186367
American Medical Association (AMA)
Chen, Shuang& Pang, Li-Ping& Lv, Jian& Xia, Zun-quan. Inexact SA Method for Constrained Stochastic Convex SDP and Application in Chinese Stock Market. Journal of Function Spaces. 2018. Vol. 2018, no. 2018, pp.1-12.
https://search.emarefa.net/detail/BIM-1186367
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1186367