Lars Kotthoff - Google Scholar

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Citations	2060	1841
h-index	17	16
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
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.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 MunichVerified 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	401	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	333	2017
Algorithm selection for combinatorial search problems: A survey L Kotthoff Data Mining and Constraint Programming, 149-190, 2016	268	2016
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	198	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	123	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	104*	2012
Package ‘FSelector’ P Romanski, L Kotthoff, ML Kotthoff Repository CRAN, 1-18, 2018	97*	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	52	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	41	2015
LLAMA: leveraging learning to automatically manage algorithms L Kotthoff arXiv preprint arXiv:1306.1031, 2013	36	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
Portfolios of subgraph isomorphism algorithms L Kotthoff, C McCreesh, C Solnon International Conference on Learning and Intelligent Optimization, 107-122, 2016	29	2016
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	27	2013
Leveraging TSP solver complementarity through machine learning P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann Evolutionary computation 26 (4), 597-620, 2018	19	2018
Using the Shapley value to analyze algorithm portfolios A Fréchette, L Kotthoff, T Michalak, T Rahwan, HH Hoos, K Leyton-Brown Thirtieth AAAI Conference on Artificial Intelligence, 2016	18	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 Algorithm Selection Competition Series 2015-17 M Lindauer, JN van Rijn, L Kotthoff arXiv preprint arXiv:1805.01214, 2018	17*	2018
The semigroups of order 10 A Distler, C Jefferson, T Kelsey, L Kotthoff International Conference on Principles and Practice of Constraint …, 2012	16	2012
The ICON challenge on algorithm selection L Kotthoff, B Hurley, B O'Sullivan AI Magazine 38 (2), 91-93, 2017	15	2017
Constraint solvers: An empirical evaluation of design decisions L Kotthoff arXiv preprint arXiv:1002.0134, 2010	14	2010

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