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Real-valued Evolutionary Optimization using a Flexible Probability Density Estimator., , and . GECCO, page 840-846. Morgan Kaufmann, (1999)Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed.. GECCO (Companion), page 2281-2286. ACM, (2009)Length Scale for Characterising Continuous Optimization Problems., and . PPSN (1), volume 7491 of Lecture Notes in Computer Science, page 407-416. Springer, (2012)Sampling Techniques and Distance Metrics in High Dimensional Continuous Landscape Analysis: Limitations and Improvements., and . IEEE Trans. Evol. Comput., 18 (3): 456-461 (2014)Using regression models for characterizing and comparing black box optimization problems., and . Swarm Evol. Comput., (2022)Clustering Problems for More Useful Benchmarking of Optimization Algorithms.. SEAL, volume 8886 of Lecture Notes in Computer Science, page 131-142. Springer, (2014)Statistical Racing Techniques for Improved Empirical Evaluation of Evolutionary Algorithms., and . PPSN, volume 3242 of Lecture Notes in Computer Science, page 172-181. Springer, (2004)A hybrid approach to parameter tuning in genetic algorithms., and . Congress on Evolutionary Computation, page 1096-1103. IEEE, (2005)Experimental results for the special session on real-parameter optimization at CEC 2005: a simple, continuous EDA., and . Congress on Evolutionary Computation, page 1792-1799. IEEE, (2005)Exploratory Analysis of Clustering Problems Using a Comparison of Particle Swarm Optimization and Differential Evolution., and . ACALCI, volume 10142 of Lecture Notes in Computer Science, page 314-325. (2017)