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Lars Kotthoff
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Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 2019
15882019
Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA
L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown
Automated machine learning: methods, systems, challenges, 81-95, 2019
8682019
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
8502016
Algorithm selection for combinatorial search problems: A survey
L Kotthoff
Data mining and constraint programming: Foundations of a cross-disciplinary …, 2016
4372016
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
2402016
mlr3: A modern object-oriented machine learning framework in R
M Lang, M Binder, J Richter, P Schratz, F Pfisterer, S Coors, Q Au, ...
Journal of Open Source Software 4 (44), 1903, 2019
2162019
An evaluation of machine learning in algorithm selection for search problems
L Kotthoff, IP Gent, I Miguel
Ai Communications 25 (3), 257-270, 2012
1032012
Fselector: selecting attributes
P Romanski, L Kotthoff
Vienna: R Foundation for Statistical Computing, 2009
882009
Proteus: A hierarchical portfolio of solvers and transformations
B Hurley, L Kotthoff, Y Malitsky, B O’Sullivan
Integration of AI and OR Techniques in Constraint Programming: 11th …, 2014
802014
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
692015
Leveraging TSP solver complementarity through machine learning
P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann
Evolutionary computation 26 (4), 597-620, 2018
682018
Machine-learning-assisted fabrication: Bayesian optimization of laser-induced graphene patterning using in-situ Raman analysis
H Wahab, V Jain, AS Tyrrell, MA Seas, L Kotthoff, PA Johnson
Carbon 167, 609-619, 2020
57*2020
The Algorithm Selection Competition Series 2015-17
M Lindauer, JN van Rijn, L Kotthoff
arXiv preprint arXiv:1805.01214, 2018
56*2018
Package ‘FSelector’
P Romanski, L Kotthoff, ML Kotthoff
URL http://cran/r-project. org/web/packages/FSelector/index. html, 2013
542013
Learning when to use lazy learning in constraint solving
IP Gent, C Jefferson, L Kotthoff, I Miguel, NCA Moore, P Nightingale, ...
ECAI 2010, 873-878, 2010
542010
LLAMA: leveraging learning to automatically manage algorithms
L Kotthoff
arXiv preprint arXiv:1306.1031, 2013
482013
Portfolios of subgraph isomorphism algorithms
L Kotthoff, C McCreesh, C Solnon
International Conference on Learning and Intelligent Optimization, 107-122, 2016
452016
Using the shapley value to analyze algorithm portfolios
A Fréchette, L Kotthoff, T Michalak, T Rahwan, H Hoos, K Leyton-Brown
Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016
442016
Automated Symmetry Breaking and Model Selection in Conjure
O Akgun, AM Frisch, IP Gent, BS Hussain, C Jefferson, L Kotthoff, I Miguel, ...
Principles and Practice of Constraint Programming: 19th International …, 2013
412013
A preliminary evaluation of machine learning in algorithm selection for search problems
L Kotthoff, I Gent, I Miguel
Proceedings of the International Symposium on Combinatorial Search 2 (1), 84-91, 2011
412011
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