Heike Trautmann

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Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyVerified email at tu-dresden.de
Christian GrimmeDepartment of Information Systems, University of Münster, GermanyVerified email at uni-muenster.de
Olaf MersmannTH KölnVerified email at p-value.net
Mike PreussUniversiteit LeidenVerified email at liacs.leidenuniv.nl
Günter RudolphProfessor in Computer Science, TU Dortmund UniversityVerified email at tu-dortmund.de
Jakob BossekPaderborn UniversityVerified email at uni-paderborn.de
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Tobias WagnerInstitute of Machining Technology (ISF), TU DortmundVerified email at isf.de
Oliver SchutzeCINVESTAV-IPNVerified email at cs.cinvestav.mx
Dennis AssenmacherGESIS - Leibniz Institute for the Social SciencesVerified email at gesis.org
Dr Jorn MehnenProfessor at the University of StrathclydeVerified email at strath.ac.uk
Frank NeumannOptimisation and Logistics, School of ComputerVerified email at adelaide.edu.au
Boris NaujoksCologne University of Applied SciencesVerified email at fh-koeln.de
Michael T.M. Emmerich (Dr. rer. nat.)Lead AI Scientist Silo.ai & Jyväskylä University, Finland & LIACS Leiden Univ. NLVerified email at liacs.nl
Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaVerified email at cs.rwth-aachen.de
Dimo BrockhoffInria, Ecole Polytechnique, Institut Polytechnique de ParisVerified email at inria.fr
Markus WagnerAssociate Professor of Computer Science, Monash University, AustraliaVerified email at monash.edu
Hao WangAssistant Professor in Leiden UniversityVerified email at liacs.leidenuniv.nl
Raphael Patrick PragerUniversity of MünsterVerified email at uni-muenster.de
Lena FrischlichDigital Democracy Centre, University of Southern DenmarkVerified email at sam.sdu.dk

Heike Trautmann

Professor of Machine Learning and Optimisation, Paderborn University, Germany

Verified email at uni-paderborn.de - Homepage

Evolutionary Computation Multiobjective Optimization Algorithm Selection and Configuration AI


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Automated algorithm selection: Survey and perspectives P Kerschke, HH Hoos, F Neumann, H Trautmann Evolutionary computation 27 (1), 3-45, 2019	386	2019
Exploratory landscape analysis O Mersmann, B Bischl, H Trautmann, M Preuss, C Weihs, G Rudolph Proceedings of the 13th annual conference on Genetic and evolutionary …, 2011	356	2011
On the properties of the R2 indicator D Brockhoff, T Wagner, H Trautmann Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	226	2012
Resampling methods for meta-model validation with recommendations for evolutionary computation B Bischl, O Mersmann, H Trautmann, C Weihs Evolutionary computation 20 (2), 249-275, 2012	207	2012
Algorithm selection based on exploratory landscape analysis and cost-sensitive learning B Bischl, O Mersmann, H Trautmann, M Preuß Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012	167	2012
Social bots: Human-like by means of human control? C Grimme, M Preuss, L Adam, H Trautmann Big data 5 (4), 279-293, 2017	166	2017
Automated algorithm selection on continuous black-box problems by combining exploratory landscape analysis and machine learning P Kerschke, H Trautmann Evolutionary computation 27 (1), 99-127, 2019	154	2019
Integration of preferences in hypervolume-based multiobjective evolutionary algorithms by means of desirability functions T Wagner, H Trautmann IEEE Transactions on Evolutionary Computation 14 (5), 688-701, 2010	133	2010
Benchmarking evolutionary algorithms: Towards exploratory landscape analysis O Mersmann, M Preuss, H Trautmann Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010	128	2010
R2-EMOA: Focused multiobjective search using R2-indicator-based selection H Trautmann, T Wagner, D Brockhoff Learning and Intelligent Optimization: 7th International Conference, LION 7 …, 2013	108	2013
Comprehensive feature-based landscape analysis of continuous and constrained optimization problems using the R-package flacco P Kerschke, H Trautmann Applications in Statistical Computing: From Music Data Analysis to …, 2019	98	2019
A novel feature-based approach to characterize algorithm performance for the traveling salesperson problem O Mersmann, B Bischl, H Trautmann, M Wagner, J Bossek, F Neumann Annals of Mathematics and Artificial Intelligence 69, 151-182, 2013	94	2013
Demystifying social bots: On the intelligence of automated social media actors D Assenmacher, L Clever, L Frischlich, T Quandt, H Trautmann, ... Social Media+ Society 6 (3), 2056305120939264, 2020	92	2020
On the distribution of the desirability index using Harrington’s desirability function H Trautmann, C Weihs Metrika 63, 207-213, 2006	92	2006
2 indicator-based multiobjective search D Brockhoff, T Wagner, H Trautmann Evolutionary Computation 23 (3), 369-395, 2015	90	2015
Optimizing data stream representation: An extensive survey on stream clustering algorithms M Carnein, H Trautmann Business & Information Systems Engineering 61, 277-297, 2019	79	2019
Detecting funnel structures by means of exploratory landscape analysis P Kerschke, M Preuss, S Wessing, H Trautmann Proceedings of the 2015 Annual Conference on Genetic and Evolutionary …, 2015	79	2015
Improving the state of the art in inexact TSP solving using per-instance algorithm selection L Kotthoff, P Kerschke, H Hoos, H Trautmann Learning and Intelligent Optimization: 9th International Conference, LION 9 …, 2015	69	2015
Leveraging TSP solver complementarity through machine learning P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann Evolutionary computation 26 (4), 597-620, 2018	68	2018
MO-ParamILS: A multi-objective automatic algorithm configuration framework A Blot, HH Hoos, L Jourdan, MÉ Kessaci-Marmion, H Trautmann Learning and Intelligent Optimization: 10th International Conference, LION …, 2016	67	2016

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