@misc{Opara_Karol_Midpoint_2013,
 author={Opara, Karol},
 copyright={Creative Commons Attribution BY 4.0 license},
 address={Warszawa},
 journal={Raport Badawczy = Research Report},
 howpublished={online},
 year={2013},
 publisher={Instytut Badań Systemowych. Polska Akademia Nauk},
 publisher={Systems Research Institute. Polish Academy of Sciences},
 language={eng},
 abstract={This paper concerns one of the state-of-the art evolutionary algorithms - CMA-ES. It consists of sampling from multivariate normal distribution, whose covariance matrix is claimed to approximate the inverse hessian of the objective function. The midpoint of this distribution should be therefore the best linear unbiased estimator of the optimum. This hypothesis was tested on the BBOB 2013 benchmark set using the standard CMA-ES implementation. Evaluation of the objective function in the midpoint neither improves nor deteriorates the performance of the algorithm. Moreover, it turns out that the standard implementation of CMA-ES is competitive but not as good as the best CMA-ES variants, which took parts in the BBOB 2009 competition.},
 title={Midpoint evaluation for CMA-ES},
 type={Text},
 URL={http://rcin.org.pl/Content/106726/PDF/RB-2013-59.pdf},
 keywords={Benchmark, Cma-es, Midpoint, Punkt środkowy},
}