All Outputs (2)

Investigating benchmark correlations when comparing algorithms with parameter tuning. (2018)
Conference Proceeding
CHRISTIE, L.A., BROWNLEE, A.E.I. and WOODWARD, J.R. 2018. Investigating benchmark correlations when comparing algorithms with parameter tuning. In Aguirre, H.E. (ed.) Proceedings of the 2018 Genetic and evolutionary computation conference companion (GECCO'18 companion), 15-19 July 2018, Kyoto, Japan. New York: Association for Computing Machinery [online], pages 209-210. Available from: https://doi.org/10.1145/3205651.3205747

Benchmarks are important for comparing performance of optimisation algorithms, but we can select instances that present our algorithm favourably, and dismiss those on which our algorithm under-performs. Also related are automated design of algorithms... Read More about Investigating benchmark correlations when comparing algorithms with parameter tuning..

Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results. (2018)
Report
CHRISTIE, L.A., BROWNLEE, A.E.I. and WOODWARD, J.R. 2018. Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results. Stirling: University of Stirling [online]. Available from: http://hdl.handle.net/1893/26956

Benchmarks are important to demonstrate the utility of optimisation algorithms, but there is controversy about the practice of benchmarking; we could select instances that present our algorithm favourably, and dismiss those on which our algorithm und... Read More about Investigating benchmark correlations when comparing algorithms with parameter tuning: detailed experiments and results..