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Heike Trautmann
Heike Trautmann
Professor of Data Science: Statistics and Optimization, Department of Information Systems
Verified email at wi.uni-muenster.de - Homepage
Title
Cited by
Cited by
Year
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
3052011
Automated algorithm selection: Survey and perspectives
P Kerschke, HH Hoos, F Neumann, H Trautmann
Evolutionary computation 27 (1), 3-45, 2019
2832019
On the properties of the R2 indicator
D Brockhoff, T Wagner, H Trautmann
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
1952012
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
1782012
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
1562012
Social bots: Human-like by means of human control?
C Grimme, M Preuss, L Adam, H Trautmann
Big data 5 (4), 279-293, 2017
1442017
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
1292010
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
1162019
Benchmarking evolutionary algorithms: Towards exploratory landscape analysis
O Mersmann, M Preuss, H Trautmann
International Conference on Parallel Problem Solving from Nature, 73-82, 2010
1082010
R2-EMOA: Focused multiobjective search using R2-indicator-based selection
H Trautmann, T Wagner, D Brockhoff
International Conference on Learning and Intelligent Optimization, 70-74, 2013
1002013
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 (2), 151-182, 2013
912013
On the distribution of the desirability index using Harrington’s desirability function
H Trautmann, C Weihs
Metrika 63 (2), 207-213, 2006
882006
2 indicator-based multiobjective search
D Brockhoff, T Wagner, H Trautmann
Evolutionary Computation 23 (3), 369-395, 2015
802015
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
712015
Comprehensive feature-based landscape analysis of continuous and constrained optimization problems using the R-package flacco
P Kerschke, H Trautmann
Applications in Statistical Computing, 93-123, 2019
692019
Improving the state of the art in inexact TSP solving using per-instance algorithm selection
L Kotthoff, P Kerschke, H Hoos, H Trautmann
International Conference on Learning and Intelligent Optimization, 202-217, 2015
652015
truncnorm: Truncated normal distribution
H Trautmann, D Steuer, O Mersmann, B Bornkamp
R package version, 1.0-7, 2014
632014
Optimizing data stream representation: An extensive survey on stream clustering algorithms
M Carnein, H Trautmann
Business & Information Systems Engineering 61 (3), 277-297, 2019
602019
Statistical methods for convergence detection of multi-objective evolutionary algorithms
H Trautmann, T Wagner, B Naujoks, M Preuss, J Mehnen
Evolutionary computation 17 (4), 493-509, 2009
602009
Leveraging TSP solver complementarity through machine learning
P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann
Evolutionary computation 26 (4), 597-620, 2018
572018
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