| OpenML: networked science in machine learning J Vanschoren, JN Van Rijn, B Bischl, L Torgo ACM SIGKDD Explorations Newsletter 15 (2), 49-60, 2014 | 351 | 2014 |
| mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... The Journal of Machine Learning Research 17 (1), 5938-5942, 2016 | 281 | 2016 |
| 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 | 148 | 2011 |
| 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 | 101 | 2012 |
| Aslib: A benchmark library for algorithm selection B Bischl, P Kerschke, L Kotthoff, M Lindauer, Y Malitsky, A Fréchette, ... Artificial Intelligence 237, 41-58, 2016 | 95 | 2016 |
| 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 | 78 | 2012 |
| mlrMBO: A modular framework for model-based optimization of expensive black-box functions B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang arXiv preprint arXiv:1703.03373, 2017 | 65* | 2017 |
| BatchJobs and BatchExperiments: Abstraction mechanisms for using R in batch environments B Bischl, M Lang, O Mersmann, C Weihs Journal of Statistical Software 64 (1), 1-25, 2015 | 56 | 2015 |
| 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 | 56 | 2013 |
| Tuning and evolution of support vector kernels P Koch, B Bischl, O Flasch, T Bartz-Beielstein, C Weihs, W Konen Evolutionary Intelligence 5 (3), 153-170, 2012 | 52 | 2012 |
| OpenML: A collaborative science platform JN Van Rijn, B Bischl, L Torgo, B Gao, V Umaashankar, S Fischer, ... Joint european conference on machine learning and knowledge discovery in …, 2013 | 50 | 2013 |
| Model-based multi-objective optimization: taxonomy, multi-point proposal, toolbox and benchmark D Horn, T Wagner, D Biermann, C Weihs, B Bischl International Conference on Evolutionary Multi-Criterion Optimization, 64-78, 2015 | 47 | 2015 |
| MOI-MBO: multiobjective infill for parallel model-based optimization B Bischl, S Wessing, N Bauer, K Friedrichs, C Weihs International Conference on Learning and Intelligent Optimization, 173-186, 2014 | 40 | 2014 |
| batchtools: Tools for R to work on batch systems M Lang, B Bischl, D Surmann The Journal of Open Source Software 2 (10), 2017 | 39 | 2017 |
| mlr: Machine Learning in R. R package version 2.9 B Bischl, M Lang, J Richter, J Bossek, L Judt, T Kuehn, E Studerus, ... | 38* | 2015 |
| Tunability: Importance of Hyperparameters of Machine Learning Algorithms. P Probst, AL Boulesteix, B Bischl Journal of Machine Learning Research 20 (53), 1-32, 2019 | 34 | 2019 |
| Personality traits predict smartphone usage C Stachl, S Hilbert, JQ Au, D Buschek, A De Luca, B Bischl, H Hussmann, ... European Journal of Personality 31 (6), 701-722, 2017 | 33 | 2017 |
| Local search and the traveling salesman problem: A feature-based characterization of problem hardness O Mersmann, B Bischl, J Bossek, H Trautmann, M Wagner, F Neumann International Conference on Learning and Intelligent Optimization, 115-129, 2012 | 30 | 2012 |
| Analyzing the bbob results by means of benchmarking concepts O Mersmann, M Preuss, H Trautmann, B Bischl, C Weihs Evolutionary computation 23 (1), 161-185, 2015 | 28 | 2015 |
| Automatic model selection for high-dimensional survival analysis M Lang, H Kotthaus, P Marwedel, C Weihs, J Rahnenführer, B Bischl Journal of Statistical Computation and Simulation 85 (1), 62-76, 2015 | 27 | 2015 |
Michel LangTU DortmundVerified email at statistik.tu-dortmund.de
