Lars Kotthoff

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Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Ian GentProfessor of Computer Science, St Andrews UniversityVerified email at st-andrews.ac.uk
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Ian MiguelUniversity of St AndrewsVerified email at st-andrews.ac.uk
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
Peter NightingaleUniversity of YorkVerified email at york.ac.uk
Barry O'SullivanSchool of Computer Science & IT, University College Cork, IrelandVerified email at cs.ucc.ie
Christopher JeffersonUniversity of St AndrewsVerified email at st-andrews.ac.uk
Jakob RichterTU DortmundVerified email at statistik.tu-dortmund.de
Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Yuri MalitskyIBM ResearchVerified email at us.ibm.com
Zachary M. JonesUniversity of WashingtonVerified email at uw.edu
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Barry HurleyUniversity College CorkVerified email at 4c.ucc.ie
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyVerified email at tu-dresden.de
Tom KelseyProfessor of Health Data Science, University of St AndrewsVerified email at st-andrews.ac.uk
Alexandre FréchettePhD Student, University of British ColumbiaVerified email at cs.ubc.ca

Lars Kotthoff

University of Wyoming

Verified email at uwyo.edu - Homepage

combinatorial optimization applied machine learning algorithm selection automated machine learning advanced materials


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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	524	2016
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	483	2019
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	428	2019
Algorithm selection for combinatorial search problems: A survey L Kotthoff Data Mining and Constraint Programming, 149-190, 2016	311	2016
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	152	2016
An evaluation of machine learning in algorithm selection for search problems L Kotthoff, IP Gent, I Miguel Ai Communications 25 (3), 257-270, 2012	115	2012
Package ‘FSelector’ P Romanski, L Kotthoff, ML Kotthoff URL http://cran/r-project. org/web/packages/FSelector/index. html, 2013	111*	2013
Proteus: A hierarchical portfolio of solvers and transformations B Hurley, L Kotthoff, Y Malitsky, B O’Sullivan International Conference on AI and OR Techniques in Constriant Programming …, 2014	55	2014
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	44	2015
LLAMA: leveraging learning to automatically manage algorithms L Kotthoff arXiv preprint arXiv:1306.1031, 2013	38	2013
Learning When to Use Lazy Learning in Constraint Solving. IP Gent, C Jefferson, L Kotthoff, I Miguel, NCA Moore, P Nightingale, ... ECAI, 873-878, 2010	36	2010
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	32	2013
Portfolios of subgraph isomorphism algorithms L Kotthoff, C McCreesh, C Solnon International Conference on Learning and Intelligent Optimization, 107-122, 2016	31	2016
Leveraging TSP solver complementarity through machine learning P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann Evolutionary computation 26 (4), 597-620, 2018	29	2018
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	25	2016
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	24	2019
The Algorithm Selection Competition Series 2015-17 M Lindauer, JN van Rijn, L Kotthoff arXiv preprint arXiv:1805.01214, 2018	23*	2018
The ICON challenge on algorithm selection L Kotthoff, B Hurley, B O'Sullivan AI Magazine 38 (2), 91-93, 2017	19	2017
Ensemble classification for constraint solver configuration L Kotthoff, I Miguel, P Nightingale International Conference on Principles and Practice of Constraint …, 2010	18	2010
The semigroups of order 10 A Distler, C Jefferson, T Kelsey, L Kotthoff International Conference on Principles and Practice of Constraint …, 2012	17	2012

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