Nikolaus Hansen

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Anne AugerInria, CMAP Ecole Polytechnique, IP ParisVerified email at inria.fr
Dimo BrockhoffInria, Ecole Polytechnique, Institut Polytechnique de ParisVerified email at inria.fr
Petros KoumoutsakosHarvard University / ETH ZurichVerified email at seas.harvard.edu
Steffen FinckVorarlberg University of Applied Sciences, Research Center Business InformaticsVerified email at fhv.at
Christian IgelDepartment of Computer Science, University of CopenhagenVerified email at diku.dk
Tea TušarResearch fellow, Jožef Stefan InstituteVerified email at ijs.si
Stefan KernGE Renewable EnergyVerified email at ge.com
Youhei AkimotoUniversity of TsukubaVerified email at cs.tsukuba.ac.jp
Kalyanmoy DebKoenig Endowed Chair Professor, Electrical and Computer Engineering, Michigan State UniversityVerified email at egr.msu.edu
Marc SchoenauerSenior Researcher, INRIAVerified email at inria.fr
Dr. P. N. Suganthan (SCI Highly Cited...EEE, NTU (Honorary Doctorate, Uni. of Maribor, 2020; BA, MA, Uni. of Cambridge, UK)Verified email at ntu.edu.sg
J. J. Liang (梁静)Zhengzhou UniversityVerified email at zzu.edu.cn
Ying-ping ChenNational Chiao Tung UniversityVerified email at cs.nctu.edu.tw
Santosh TiwariVehicle Optimization Engineer at General MotorsVerified email at gm.com
Dirk V. ArnoldProfessor, Faculty of Computer Science, Dalhousie UniversityVerified email at cs.dal.ca
Artem R. OganovSkolkovo Institute of Science and Technology, RussiaVerified email at skoltech.ru
Olaf MersmannTH KölnVerified email at p-value.net
Petr PošíkResearcher, Czech Technical University in PragueVerified email at fel.cvut.cz
Asma AtamnaRuhr-Universität BochumVerified email at ini.rub.de
Lino GuzzellaETH ZurichVerified email at ethz.ch

Nikolaus Hansen

Inria & Institut Polytechnique de Paris, France

Verified email at Inria.fr - Homepage

Computational Intelligence Evolutionary Algorithms Evolutionary Computation Machine Learning Numerical Optimization


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Completely derandomized self-adaptation in evolution strategies N Hansen, A Ostermeier Evolutionary computation 9 (2), 159-195, 2001	3716	2001
Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization PN Suganthan, N Hansen, JJ Liang, K Deb, YP Chen, A Auger, S Tiwari KanGAL report 2005005 (2005), 2005, 2005	2302	2005
Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES) N Hansen, SD Müller, P Koumoutsakos Evolutionary computation 11 (1), 1-18, 2003	1873	2003
The CMA evolution strategy: a comparing review N Hansen Towards a new evolutionary computation, 75-102, 2006	1779	2006
Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation N Hansen, A Ostermeier Proceedings of IEEE international conference on evolutionary computation …, 1996	1187	1996
A restart CMA evolution strategy with increasing population size A Auger, N Hansen 2005 IEEE congress on evolutionary computation 2, 1769-1776, 2005	986	2005
The CMA evolution strategy: A tutorial N Hansen Inria, 2005	898*	2005
Evaluating the CMA evolution strategy on multimodal test functions N Hansen, S Kern International Conference on Parallel Problem Solving from Nature, 282-291, 2004	846	2004
USPEX—Evolutionary crystal structure prediction CW Glass, AR Oganov, N Hansen Computer physics communications 175 (11-12), 713-720, 2006	832	2006
Covariance matrix adaptation for multi-objective optimization C Igel, N Hansen, S Roth Evolutionary computation 15 (1), 1-28, 2007	759	2007
Real-parameter black-box optimization benchmarking 2009: Noiseless functions definitions N Hansen, S Finck, R Ros, A Auger INRIA, 2009	463	2009
Real-parameter black-box optimization benchmarking 2010: Experimental setup N Hansen, A Auger, S Finck, R Ros INRIA, 2010	439	2010
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009 N Hansen, A Auger, R Ros, S Finck, P Pošík Proceedings of the 12th annual conference companion on Genetic and …, 2010	352	2010
Performance evaluation of an advanced local search evolutionary algorithm A Auger, N Hansen 2005 IEEE congress on evolutionary computation 2, 1777-1784, 2005	311	2005
A method for handling uncertainty in evolutionary optimization with an application to feedback control of combustion N Hansen, ASP Niederberger, L Guzzella, P Koumoutsakos IEEE Transactions on Evolutionary Computation 13 (1), 180-197, 2008	301	2008
Learning probability distributions in continuous evolutionary algorithms–a comparative review S Kern, SD Müller, N Hansen, D Büche, J Ocenasek, P Koumoutsakos Natural Computing 3 (1), 77-112, 2004	280	2004
A derandomized approach to self-adaptation of evolution strategies A Ostermeier, A Gawelczyk, N Hansen Evolutionary Computation 2 (4), 369-380, 1994	269	1994
Benchmarking a BI-population CMA-ES on the BBOB-2009 function testbed N Hansen Proceedings of the 11th Annual Conference Companion on Genetic and …, 2009	260	2009
Real-parameter black-box optimization benchmarking 2009: Presentation of the noiseless functions S Finck, N Hansen, R Ros, A Auger Technical Report 2009/20, Research Center PPE, 2009. Updated February, 2010	230	2010
A simple modification in CMA-ES achieving linear time and space complexity R Ros, N Hansen International Conference on Parallel Problem Solving from Nature, 296-305, 2008	229	2008

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