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Lars Kotthoff
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Процитировано
Год
Automated machine learning: methods, systems, challenges
F Hutter, L Kotthoff, J Vanschoren
Springer Nature, 2019
9362019
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
7102016
Auto-WEKA: Automatic model selection and hyperparameter optimization in WEKA
L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown
Automated machine learning, 81-95, 2019
6862019
Algorithm selection for combinatorial search problems: A survey
L Kotthoff
Data mining and constraint programming, 149-190, 2016
3742016
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
2002016
An evaluation of machine learning in algorithm selection for search problems
L Kotthoff, IP Gent, I Miguel
Ai Communications 25 (3), 257-270, 2012
1332012
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
992019
Fselector: selecting attributes
P Romanski, L Kotthoff
Vienna: R Foundation for Statistical Computing, 2009
892009
Proteus: A hierarchical portfolio of solvers and transformations
B Hurley, L Kotthoff, Y Malitsky, B O’Sullivan
International Conference on Integration of Constraint Programming …, 2014
692014
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
612015
Leveraging TSP solver complementarity through machine learning
P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann
Evolutionary computation 26 (4), 597-620, 2018
522018
LLAMA: leveraging learning to automatically manage algorithms
L Kotthoff
arXiv preprint arXiv:1306.1031, 2013
462013
Package ‘FSelector’
P Romanski, L Kotthoff, ML Kotthoff
URL http://cran/r-project. org/web/packages/FSelector/index. html, 2013
462013
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
442010
The Algorithm Selection Competition Series 2015-17
M Lindauer, JN van Rijn, L Kotthoff
arXiv preprint arXiv:1805.01214, 2018
41*2018
Portfolios of subgraph isomorphism algorithms
L Kotthoff, C McCreesh, C Solnon
International Conference on Learning and Intelligent Optimization, 107-122, 2016
392016
Automated symmetry breaking and model selection in Conjure
O Akgun, AM Frisch, IP Gent, BS Hussain, C Jefferson, L Kotthoff, I Miguel, ...
International Conference on Principles and Practice of Constraint …, 2013
362013
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
342016
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
28*2020
The ICON challenge on algorithm selection
L Kotthoff, B Hurley, B O'Sullivan
AI Magazine 38 (2), 91-93, 2017
252017
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