How experimental algorithmics can benefit from Mayo’s extensions to Neyman–Pearson theory of testing

Author:

Bartz-Beielstein Thomas

Publisher

Springer Science and Business Media LLC

Subject

General Social Sciences,Philosophy

Reference15 articles.

1. Bartz-Beielstein T. (2006). Experimental research in evolutionary computation—The new experimentalism. Berlin, Heidelberg, New York: Springer.

2. Bartz-Beielstein, T., & Preuss, M. (2004). CEC tutorial on experimental research in evolutionary computation. In IEEE Congress on Evolutionary Computation, Tutorial Program. Tutorials given at CEC in 2004 and 2005.

3. Bartz-Beielstein, T., & Preuss, M. (2005). GECCO tutorial on experimental research in evolutionary computation. In 2005 Genetic and Evolutionary Computation Conference, Tutorial Program. Tutorials given at GECCO in 2005, 2006, and 2007.

4. Bartz-Beielstein, T., & Preuss, M. (2006a). Considerations of budget allocation for sequential parameter pptimization (SPO). In Workshop on Empirical Methods for the Analysis of Algorithms (EMAA), Tutorial Program. Held in conjunction with the International Conference on Parallel Problem Solving From Nature (PPSN IX) (pp. 35–40).

5. Bartz-Beielstein, T., & Preuss, M. (2006b). Sequential parameter optimization (SPO) and the role of tuning in experimental analysis. In Workshop on Empirical Methods for the Analysis of Algorithms (EMAA). Held in conjunction with the International Conference on Parallel Problem Solving From Nature (PPSN IX) (pp. 5–6). Invited talk

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