Ghoshdastidar, Debarghya ; Dukkipati, Ambedkar ; Bhatnagar, Shalabh (2012) q-Gaussian based Smoothed Functional algorithms for stochastic optimization In: IEEE International Symposium on Information Theory Proceedings, 1-6 July 2012, Cambridge, MA, USA.
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Official URL: http://doi.org/10.1109/ISIT.2012.6283013
Related URL: http://dx.doi.org/10.1109/ISIT.2012.6283013
Abstract
The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Source: | Copyright of this article belongs to Institute of Electrical and Electronics Engineers. |
| ID Code: | 116678 |
| Deposited On: | 12 Apr 2021 07:22 |
| Last Modified: | 12 Apr 2021 07:22 |
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