Theo dõi
Heike Trautmann
Heike Trautmann
Professor of Machine Learning and Optimisation, Paderborn University, Germany
Email được xác minh tại uni-paderborn.de - Trang chủ
Tiêu đề
Trích dẫn bởi
Trích dẫn bởi
Năm
Automated algorithm selection: Survey and perspectives
P Kerschke, HH Hoos, F Neumann, H Trautmann
Evolutionary computation 27 (1), 3-45, 2019
5262019
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
4372011
On the properties of the R2 indicator
D Brockhoff, T Wagner, H Trautmann
Proceedings of the 14th annual conference on Genetic and evolutionary …, 2012
2522012
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
2222012
Social bots: Human-like by means of human control?
C Grimme, M Preuss, L Adam, H Trautmann
Big data 5 (4), 279-293, 2017
2092017
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
2022019
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
1822012
Benchmarking evolutionary algorithms: Towards exploratory landscape analysis
O Mersmann, M Preuss, H Trautmann
Parallel Problem Solving from Nature, PPSN XI: 11th International Conference …, 2010
1532010
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
1432020
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
1432010
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
1382019
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
1152013
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
1042015
2 indicator-based multiobjective search
D Brockhoff, T Wagner, H Trautmann
Evolutionary computation 23 (3), 369-395, 2015
1022015
Leveraging TSP solver complementarity through machine learning
P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann
Evolutionary computation 26 (4), 597-620, 2018
992018
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
992013
On the distribution of the desirability index using Harrington’s desirability function
H Trautmann, C Weihs
Metrika 63, 207-213, 2006
992006
Optimizing data stream representation: An extensive survey on stream clustering algorithms
M Carnein, H Trautmann
Business & Information Systems Engineering 61, 277-297, 2019
962019
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
842016
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
822015
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