Lars Kotthoff

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Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyEmail yang diverifikasi di cs.uni-freiburg.de
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichEmail yang diverifikasi di stat.uni-muenchen.de
Joaquin VanschorenEindhoven University of TechnologyEmail yang diverifikasi di tue.nl
Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaEmail yang diverifikasi di cs.rwth-aachen.de
Ian GentProfessor of Computer Science, St Andrews UniversityEmail yang diverifikasi di st-andrews.ac.uk
Michel LangTU Dortmund; LMU MunichEmail yang diverifikasi di statistik.tu-dortmund.de
Ian MiguelUniversity of St AndrewsEmail yang diverifikasi di st-andrews.ac.uk
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairEmail yang diverifikasi di cs.ubc.ca
Jakob RichterTU DortmundEmail yang diverifikasi di statistik.tu-dortmund.de
Peter NightingaleSenior Lecturer, Department of Computer Science, University of YorkEmail yang diverifikasi di york.ac.uk
Giuseppe CasalicchioSenior Lecturer and Researcher, LMU Munich, Munich Center for Machine LearningEmail yang diverifikasi di campus.lmu.de
Barry O'SullivanSchool of Computer Science & IT, University College Cork, IrelandEmail yang diverifikasi di cs.ucc.ie
Christopher JeffersonUniversity of St AndrewsEmail yang diverifikasi di st-andrews.ac.uk
Yuri MalitskyIBM ResearchEmail yang diverifikasi di us.ibm.com
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchEmail yang diverifikasi di ai.uni-hannover.de
Florian Pfistererhemato GmbH, Ludwig Maximilian University of MunichEmail yang diverifikasi di stat.uni-muenchen.de
Zachary M. JonesMetaEmail yang diverifikasi di fb.com
Patrick SchratzPhD, Friedrich Schiller University JenaEmail yang diverifikasi di uni-jena.de
Pascal KerschkeProfessor of Big Data Analytics in Transportation, TU Dresden, and ScaDS.AIEmail yang diverifikasi di tu-dresden.de
Hud WahabUniversity of WyomingEmail yang diverifikasi di uwyo.edu

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Lars Kotthoff

University of Wyoming

Email yang diverifikasi di uwyo.edu - Beranda

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


Judul Urutkan menurut kutipan Urutkan menurut tahun Urutkan menurut judul	Dikutip oleh Dikutip oleh	Tahun
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	2337	2019
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown Journal of Machine Learning Research 18 (25), 1-5, 2017	1036	2017
mlr: Machine Learning in R B Bischl, M Lang, L Kotthoff, J Schiffner, J Richter, E Studerus, ... Journal of Machine Learning Research 17 (170), 1-5, 2016	981	2016
Algorithm selection for combinatorial search problems: A survey L Kotthoff Data mining and constraint programming: Foundations of a cross-disciplinary …, 2016	495	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	373	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	308	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	106	2012
Leveraging TSP solver complementarity through machine learning P Kerschke, L Kotthoff, J Bossek, HH Hoos, H Trautmann Evolutionary computation 26 (4), 597-620, 2018	99	2018
Fselector: selecting attributes P Romanski, L Kotthoff Vienna: R Foundation for Statistical Computing, 2009	96	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	92	2014
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	86	2020
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	82	2015
The Algorithm Selection Competition Series 2015-17 M Lindauer, JN van Rijn, L Kotthoff arXiv preprint arXiv:1805.01214, 2018	78*	2018
Package ‘FSelector’ P Romanski, L Kotthoff, ML Kotthoff URL http://cran/r-project. org/web/packages/FSelector/index. html, 2013	58	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	58	2010
Portfolios of subgraph isomorphism algorithms L Kotthoff, C McCreesh, C Solnon International Conference on Learning and Intelligent Optimization, 107-122, 2016	55	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	52	2016
LLAMA: leveraging learning to automatically manage algorithms L Kotthoff arXiv preprint arXiv:1306.1031, 2013	52	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	43	2011
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

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