Frank Hutter

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Citations	59461	53364
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Holger HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaVerified email at cs.rwth-aachen.de
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified email at cs.ubc.ca
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
Katharina EggenspergerEarly Career Group Leader "AutoML for Science" | University of TübingenVerified email at uni-tuebingen.de
Matthias FeurerLMU Munich & Munich Center for Machine LearningVerified email at stat.uni-muenchen.de
Aaron KleinAWS Research BerlinVerified email at amazon.com
Ilya LoshchilovVerified email at inria.fr
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Jost Tobias SpringenbergAlbert-Ludwigs-Universität FreiburgVerified email at informatik.uni-freiburg.de
Lin XuUniversity of British ColumbiaVerified email at cs.ubc.ca
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Tonio BallNeuromedical AI Lab Uni Freiburg, NeuroMentum AI (CEO)Verified email at uniklinik-freiburg.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Wolfram BurgardProfessor of Computer Science, Technical University of NurembergVerified email at utn.de
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Michael TangermannDonders Insitute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, andVerified email at donders.ru.nl
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Richard DeardenReader in Intelligent Robotics, University of BirminghamVerified email at cs.bham.ac.uk
Philipp HennigUniversity of TübingenVerified email at uni-tuebingen.de

Frank Hutter

Professor of Computer Science, University of Freiburg, Germany

Verified email at cs.uni-freiburg.de - Homepage

AutoML Meta-Learning Neural Architecture Search Deep Learning Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Decoupled weight decay regularization I Loshchilov, F Hutter arXiv preprint arXiv:1711.05101, 2017	13767	2017
Sgdr: Stochastic gradient descent with warm restarts I Loshchilov, F Hutter arXiv preprint arXiv:1608.03983, 2016	6482	2016
Sequential model-based optimization for general algorithm configuration F Hutter, HH Hoos, K Leyton-Brown Learning and Intelligent Optimization: 5th International Conference, LION 5 …, 2011	2927	2011
Neural architecture search: A survey T Elsken, JH Metzen, F Hutter The Journal of Machine Learning Research 20 (1), 1997-2017, 2019	2731	2019
Efficient and robust automated machine learning M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter Advances in neural information processing systems 28, 2015	2470	2015
Deep learning with convolutional neural networks for EEG decoding and visualization RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ... Human brain mapping 38 (11), 5391-5420, 2017	2170	2017
Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms C Thornton, F Hutter, HH Hoos, K Leyton-Brown Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	1865	2013
Automated machine learning: methods, systems, challenges F Hutter, L Kotthoff, J Vanschoren Springer Nature, 2019	1604	2019
Hyperparameter optimization M Feurer, F Hutter Automated machine learning: Methods, systems, challenges, 3-33, 2019	1210	2019
ParamILS: an automatic algorithm configuration framework F Hutter, HH Hoos, K Leyton-Brown, T Stützle Journal of artificial intelligence research 36, 267-306, 2009	1207	2009
SATzilla: portfolio-based algorithm selection for SAT L Xu, F Hutter, HH Hoos, K Leyton-Brown Journal of artificial intelligence research 32, 565-606, 2008	1098	2008
BOHB: Robust and efficient hyperparameter optimization at scale S Falkner, A Klein, F Hutter International conference on machine learning, 1437-1446, 2018	1043	2018
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	860	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, 81-95, 2019	860	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	860	2017
Bayesian optimization in a billion dimensions via random embeddings Z Wang, F Hutter, M Zoghi, D Matheson, N De Feitas Journal of Artificial Intelligence Research 55, 361-387, 2016	752	2016
Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves T Domhan, JT Springenberg, F Hutter Twenty-fourth international joint conference on artificial intelligence, 2015	703	2015
Nas-bench-101: Towards reproducible neural architecture search C Ying, A Klein, E Christiansen, E Real, K Murphy, F Hutter International conference on machine learning, 7105-7114, 2019	635	2019
Fast bayesian optimization of machine learning hyperparameters on large datasets A Klein, S Falkner, S Bartels, P Hennig, F Hutter Artificial intelligence and statistics, 528-536, 2017	635	2017
Efficient multi-objective neural architecture search via lamarckian evolution T Elsken, JH Metzen, F Hutter arXiv preprint arXiv:1804.09081, 2018	550	2018

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