Name
Title | ||
|---|---|---|
Gradient-Based Myopic Allocation Policy: An Efficient Sampling Procedure in a Low-Confidence Scenario. |
Abstract | ||
|---|---|---|
In this note, we study a simulation optimization problem of selecting the alternative with the best performance from a finite set, or a so-called ranking and selection problem, in a special low-confidence scenario. The most popular sampling allocation procedures in ranking and selection do not perform well in this scenario, because they all ignore certain induced correlations that significantly af... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TAC.2017.2776606 | IEEE Transactions on Automatic Control |
Keywords | Field | DocType |
Resource management,Correlation,Bayes methods,Gaussian distribution,Taylor series | Resource management,Low Confidence,Mathematical optimization,Finite set,Ranking,Correlation,Sampling (statistics),Optimization problem,Mathematics,Taylor series | Journal |
Volume | Issue | ISSN |
63 | 9 | 0018-9286 |
Citations | PageRank | References |
1 | 0.35 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yijie Peng | 1 | 32 | 12.59 |
| Chun-Hung Chen | 2 | 1095 | 117.31 |
| Michael C. Fu | 3 | 1161 | 128.16 |
| Jian-Qiang Hu | 4 | 25 | 6.52 |