Inexact SA Method for Constrained Stochastic Convex SDP and Application in Chinese Stock Market
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 so...
| Published in: | Journal of Function Spaces |
|---|---|
| Main Authors: | , , , |
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Online Access: | http://dx.doi.org/10.1155/2018/3742575 |