Frank Hutter - Google Scholar Citations

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	All	Since 2015
Citations	12166	9510
h-index	52	44
i10-index	94	92

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Co-authors

Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Kevin Leyton-BrownProfessor of Computer Science, University of British Columbia; Canada CIFAR AI Chair, AmiiVerified email at cs.ubc.ca
Aaron KleinAmazon Research BerlinVerified email at cs.uni-freiburg.de
Katharina EggenspergerPhD Student, Machine Learning Lab, University of FreiburgVerified email at informatik.uni-freiburg.de
Matthias FeurerMachine Learning group, University of FreiburgVerified email at informatik.uni-freiburg.de
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Lin XuUniversity of British ColumbiaVerified email at cs.ubc.ca
Jost Tobias SpringenbergAlbert-Ludwigs-Universität FreiburgVerified email at informatik.uni-freiburg.de
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Ilya LoshchilovVerified email at inria.fr
Tonio BallHead of Neuromedical AI Lab FreiburgVerified email at uniklinik-freiburg.de
Lars KotthoffUniversity of WyomingVerified email at uwyo.edu
Thomas StützleF.R.S.-FNRS Research Director, Université Libre de Bruxelles (ULB)Verified email at ulb.ac.be
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Wolfram BurgardProfessor of Computer Science, University of FreiburgVerified email at informatik.uni-freiburg.de
Richard DeardenReader in Intelligent Robotics, University of BirminghamVerified email at cs.bham.ac.uk
Manuel BlumUniversity of FreiburgVerified email at informatik.uni-freiburg.de
Nando de FreitasCIFAR & DeepMindVerified email at google.com
Kevin MurphyResearch Scientist, GoogleVerified email at google.com
Michael TangermannBrain State Decoding Lab and Autonomous Intelligent Systems Lab, University of Freiburg, GermanyVerified email at blbt.uni-freiburg.de

Frank Hutter

Professor of Computer Science, University of Freiburg, Germany

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

Machine Learning Deep Learning Artificial Intelligence Automated Algorithm Design Combinatorial Optimization


Title	Cited by	Year
Sequential model-based optimization for general algorithm configuration F Hutter, HH Hoos, K Leyton-Brown International conference on learning and intelligent optimization, 507-523, 2011	1235	2011
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	785	2013
ParamILS: an automatic algorithm configuration framework F Hutter, HH Hoos, K Leyton-Brown, T Stützle Journal of Artificial Intelligence Research 36, 267-306, 2009	784	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	754	2008
Sgdr: Stochastic gradient descent with warm restarts I Loshchilov, F Hutter arXiv preprint arXiv:1608.03983, 2016	622	2016
Efficient and robust automated machine learning M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter Advances in neural information processing systems, 2962-2970, 2015	606	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	446	2017
Algorithm runtime prediction: Methods & evaluation F Hutter, L Xu, HH Hoos, K Leyton-Brown Artificial Intelligence 206, 79-111, 2014	296	2014
Automatic algorithm configuration based on local search F Hutter, HH Hoos, T Stützle Aaai 7, 1152-1157, 2007	292	2007
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	243	2017
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	238	2015
Scaling and probabilistic smoothing: Efficient dynamic local search for SAT F Hutter, D Tompkins, H Hoos Principles and Practice of Constraint Programming-CP 2002, 241-249, 2002	236	2002
Initializing Bayesian Hyperparameter Optimization via Meta-Learning. M Feurer, JT Springenberg, F Hutter AAAI, 1128-1135, 2015	221*	2015
Neural architecture search: A survey T Elsken, JH Metzen, F Hutter arXiv preprint arXiv:1808.05377, 2018	210	2018
Decoupled weight decay regularization I Loshchilov, F Hutter arXiv preprint arXiv:1711.05101, 2017	191*	2017
Bayesian optimization in high dimensions via random embeddings Z Wang, M Zoghi, F Hutter, D Matheson, N De Freitas Twenty-Third International Joint Conference on Artificial Intelligence, 2013	184	2013
Performance prediction and automated tuning of randomized and parametric algorithms F Hutter, Y Hamadi, HH Hoos, K Leyton-Brown International Conference on Principles and Practice of Constraint …, 2006	181	2006
Towards an empirical foundation for assessing bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... NIPS workshop on Bayesian Optimization in Theory and Practice 10, 3, 2013	177	2013
Fast bayesian optimization of machine learning hyperparameters on large datasets A Klein, S Falkner, S Bartels, P Hennig, F Hutter arXiv preprint arXiv:1605.07079, 2016	162	2016
A new algorithm for RNA secondary structure design M Andronescu, AP Fejes, F Hutter, HH Hoos, A Condon Journal of molecular biology 336 (3), 607-624, 2004	160	2004

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