Lars Kotthoff - Google Scholar

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Citations	2192	1973
h-index	17	17
i10-index	27	19

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Co-authors

Ian GentProfessor of Computer Science, St Andrews UniversityVerified email at st-andrews.ac.uk
Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Ian MiguelUniversity of St AndrewsVerified 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
Peter NightingaleUniversity of YorkVerified email at york.ac.uk
Kevin Leyton-BrownProfessor of Computer Science, University of British Columbia; Canada CIFAR AI Chair, AmiiVerified email at cs.ubc.ca
Christopher JeffersonUniversity of St AndrewsVerified email at st-andrews.ac.uk
Barry O'SullivanSchool of Computer Science & IT, University College Cork, IrelandVerified email at cs.ucc.ie
Jakob RichterPh.D. Candidate, TU DortmundVerified email at statistik.tu-dortmund.de
Michel LangTU DortmundVerified 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 KerschkeUniversity of MünsterVerified email at uni-muenster.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


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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	429	2016
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown The Journal of Machine Learning Research 18 (1), 826-830, 2017	355	2017
Algorithm selection for combinatorial search problems: A survey L Kotthoff Data Mining and Constraint Programming, 149-190, 2016	278	2016
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	234	2019
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	132	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	107*	2012
Package ‘FSelector’ P Romanski, L Kotthoff, ML Kotthoff Repository CRAN, 1-18, 2018	98*	2018
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	53	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	43	2015
LLAMA: leveraging learning to automatically manage algorithms L Kotthoff arXiv preprint arXiv:1306.1031, 2013	37	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	35	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	31	2013
Portfolios of subgraph isomorphism algorithms L Kotthoff, C McCreesh, C Solnon International Conference on Learning and Intelligent Optimization, 107-122, 2016	29	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	20	2018
The Algorithm Selection Competition Series 2015-17 M Lindauer, JN van Rijn, L Kotthoff arXiv preprint arXiv:1805.01214, 2018	19*	2018
Using the Shapley Value to Analyze Algorithm Portfolios. A Fréchette, L Kotthoff, TP Michalak, T Rahwan, HH Hoos, ... AAAI, 3397-3403, 2016	19	2016
Ensemble classification for constraint solver configuration L Kotthoff, I Miguel, P Nightingale International Conference on Principles and Practice of Constraint …, 2010	18	2010
The ICON challenge on algorithm selection L Kotthoff, B Hurley, B O'Sullivan AI Magazine 38 (2), 91-93, 2017	17	2017
The semigroups of order 10 A Distler, C Jefferson, T Kelsey, L Kotthoff International Conference on Principles and Practice of Constraint …, 2012	17	2012
Constraint solvers: An empirical evaluation of design decisions L Kotthoff arXiv preprint arXiv:1002.0134, 2010	14	2010

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