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Benchmarking sep-CMA-ES on the BBOB-2009 function testbed
2009
Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09
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doi:10.1145/1570256.1570340
dblp:conf/gecco/Ros09d
fatcat:ltyuoyavdba6fntywaa4nsb7h4
Benchmarking sep-CMA-ES on the BBOB-2009 noisy testbed
2009
Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
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A partly time and space linear CMA-ES is benchmarked on the BBOB-2009 noisy function testbed. ...
This algorithm with a multistart strategy with increasing population size solves 10 functions out of 30 in 20-D. ...
A mixed strategy of using sep-CMA-ES and CMA-ES is proposed here and benchmarked on a noisy function testbed. ...
doi:10.1145/1570256.1570341
dblp:conf/gecco/Ros09e
fatcat:xz7uxw3rdzblljtdjvgppslmyu
Benchmarking the (1,4)-CMA-ES with mirrored sampling and sequential selection on the noisy BBOB-2010 testbed
2010
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10
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In this paper, we benchmark the (1,4 s m )-CMA-ES which implements mirrored samples and sequential selection on the BBOB-2010 noisy testbed. ...
Moreover, on 7 of the 8 functions that are solved by the (1,4 s m )-CMA-ES in 20D, we see a large improvement over the best algorithm of the BBOB-2009 benchmarking for the corresponding functions-ranging ...
Acknowledgments This work receives support by the French national research agency (ANR) within the SYSCOMM project ANR-08-SYSC-017 and within the COSINUS project ANR-08-COSI-007-12. ...
doi:10.1145/1830761.1830782
dblp:conf/gecco/AugerBH10j
fatcat:lqdbaumiwjho3jvpypeebxzfjy
Investigating the impact of sequential selection in the (1,4)-CMA-ES on the noisy BBOB-2010 testbed
2010
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10
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This paper investigates the impact of the application of sequential selection to the (1,4)-CMA-ES on the BBOB-2010 noisy benchmark testbed. ...
Moreover, the (1,4 s )-CMA-ES shows shorter expected running times on 6 functions of up to 32% compared to the functionwise best algorithm of the BBOB-2009 benchmarking (in 20D and for a target value of ...
the BBOB-2009 benchmarking on 6 functions (in 20D and for a target value of 10 −7 ). ...
doi:10.1145/1830761.1830780
dblp:conf/gecco/AugerBH10h
fatcat:iviktrh3tvfcdd4j3dp5g46agq
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009
2010
Proceedings of the 12th annual conference comp on Genetic and evolutionary computation - GECCO '10
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This paper presents results of the BBOB-2009 benchmarking of 31 search algorithms on 24 noiseless functions in a black-box optimization scenario in continuous domain. ...
Searching in larger dimension and multi-modal functions appears to be more difficult. The choice of the best algorithm also depends remarkably on the available budget of function evaluations. ...
Technical Report 2009/20, Research Center PPE, 2009. [11] M. Gallagher. Black-box optimization benchmarking: results for the BayEDAcG algorithm on the noiseless function testbed. ...
doi:10.1145/1830761.1830790
dblp:conf/gecco/HansenARFP10
fatcat:thucs3rocfg6vmwtxfudxypqee
Permuted Orthogonal Block-Diagonal Transformation Matrices for Large Scale Optimization Benchmarking
2016
Proceedings of the 2016 on Genetic and Evolutionary Computation Conference - GECCO '16
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We investigate the impact of the different parameters of the transformation on its shape and on the difficulty of the problems for separable CMA-ES. ...
We illustrate the use of the above defined transformation in the BBOB-2009 testbed as replacement for the expensive orthogonal (rotation) matrices. ...
This work was supported by the grant ANR-12-MONU-0009 (NumBBO) of the French National Research Agency. ...
doi:10.1145/2908812.2908937
dblp:conf/gecco/ElHaraAH16
fatcat:4h6lerg4zrbctf2djodyyoh3v4
Benchmarking separable natural evolution strategies on the noiseless and noisy black-box optimization testbeds
2012
Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12
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It is thus quite similar to sep-CMA-ES [9] . ...
This report provides the the most extensive empirical results on that algorithm to date, on both the noise-free and noisy BBOB testbeds. any type of distribution, by ascending the gradient towards higher ...
Acknowlegements The author wants to thank the organizers of the BBOB workshop for providing such a well-designed benchmark setup, and especially such high-quality post-processing utilities. ...
doi:10.1145/2330784.2330815
dblp:conf/gecco/Schaul12a
fatcat:snp6w5ydejcf3mxrefmztczvwm
Population-based heuristic algorithms for continuous and mixed discrete-continuous optimization problems
2015
4OR
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(iii) we extend CMA-ES to tackle mixed discrete-continuous optimization problems. ...
We also propose iCMAES-ILS, a hybrid algorithm that loosely couples IPOP-CMA-ES, a CMA-ES variant that uses a restart schema coupled with an increasing population iii v me to apply for a fellowship from ...
IPOP-CMA-ES embeds CMA-ES into a restart mechanism that increases the population size between successive runs of CMA-ES. ...
doi:10.1007/s10288-015-0285-8
fatcat:fbdeu2lx4ngghdyqenamhfckry