Lars Kotthoff

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Bernd BischlChair of Statistical Learning and Data Science, LMU MunichDirección de correo verificada de stat.uni-muenchen.de
Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaDirección de correo verificada de cs.rwth-aachen.de
Joaquin VanschorenEindhoven University of TechnologyDirección de correo verificada de tue.nl
Frank HutterProfessor of Computer Science, University of Freiburg, GermanyDirección de correo verificada de cs.uni-freiburg.de
Ian GentProfessor of Computer Science, St Andrews UniversityDirección de correo verificada de st-andrews.ac.uk
Ian MiguelUniversity of St AndrewsDirección de correo verificada de st-andrews.ac.uk
Michel LangTU Dortmund; LMU MunichDirección de correo verificada de statistik.tu-dortmund.de
Jakob RichterTU DortmundDirección de correo verificada de statistik.tu-dortmund.de
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairDirección de correo verificada de cs.ubc.ca
Peter NightingaleUniversity of YorkDirección de correo verificada de york.ac.uk
Barry O'SullivanSchool of Computer Science & IT, University College Cork, IrelandDirección de correo verificada de cs.ucc.ie
Christopher JeffersonUniversity of St AndrewsDirección de correo verificada de st-andrews.ac.uk
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningDirección de correo verificada de campus.lmu.de
Yuri MalitskyIBM ResearchDirección de correo verificada de us.ibm.com
Zachary M. JonesMetaDirección de correo verificada de fb.com
Florian PfistererLudwig Maximilian University of MunichDirección de correo verificada de stat.uni-muenchen.de
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchDirección de correo verificada de ai.uni-hannover.de
Patrick SchratzPhD, Friedrich Schiller University JenaDirección de correo verificada de uni-jena.de
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, GermanyDirección de correo verificada de tu-dresden.de
Hud WahabUniversity of WyomingDirección de correo verificada de uwyo.edu

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Lars Kotthoff

University of Wyoming

Dirección de correo verificada de uwyo.edu - Página principal

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


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	1588	2019
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	868	2019
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	851	2016
Algorithm selection for combinatorial search problems: A survey L Kotthoff Data mining and constraint programming: Foundations of a cross-disciplinary …, 2016	437	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	240	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	216	2019
An evaluation of machine learning in algorithm selection for search problems L Kotthoff, IP Gent, I Miguel Ai Communications 25 (3), 257-270, 2012	103	2012
Fselector: selecting attributes P Romanski, L Kotthoff Vienna: R Foundation for Statistical Computing, 2009	88	2009
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	80	2014
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	69	2015
Leveraging TSP solver complementarity through machine learning P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann Evolutionary computation 26 (4), 597-620, 2018	68	2018
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	54	2013
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	54	2010
LLAMA: leveraging learning to automatically manage algorithms L Kotthoff arXiv preprint arXiv:1306.1031, 2013	48	2013
Portfolios of subgraph isomorphism algorithms L Kotthoff, C McCreesh, C Solnon International Conference on Learning and Intelligent Optimization, 107-122, 2016	45	2016
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	44	2016
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	41	2013
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	41	2011

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