Matthias Feurer - Google Scholar Citations

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	All	Since 2015
Citations	1338	1323
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201420152016201720182019202015 43 97 149 300 594 138

Co-authors

Frank HutterProfessor of Computer Science, University of Freiburg, GermanyVerified email at cs.uni-freiburg.de
Katharina EggenspergerPhD Student, Machine Learning Lab, University of FreiburgVerified email at informatik.uni-freiburg.de
Jost Tobias SpringenbergAlbert-Ludwigs-Universität FreiburgVerified email at informatik.uni-freiburg.de
Aaron KleinAmazon Research BerlinVerified email at cs.uni-freiburg.de
Manuel BlumUniversity of FreiburgVerified email at informatik.uni-freiburg.de
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Kevin Leyton-BrownProfessor of Computer Science, University of British Columbia; Canada CIFAR AI Chair, AmiiVerified email at cs.ubc.ca
James BergstraVerified email at uwaterloo.ca
Jasper SnoekGoogle BrainVerified email at google.com
Holger HoosLeiden University, The Netherlands & University of British Columbia, CanadaVerified email at liacs.nl
Bernd BischlHead of "Computational Statistics" Group, LMU MunichVerified email at stat.uni-muenchen.de
Michel LangTU DortmundVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioLMU MünchenVerified email at campus.lmu.de
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
André BiedenkappPhD candidate, University of FreiburgVerified email at cs.uni-freiburg.de
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Eytan BakshyEmpiricist, FacebookVerified email at fb.com
Andreas Christian MuellerColumbia UniversityVerified email at columbia.edu

Matthias Feurer

Machine Learning group, University of Freiburg

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

Hyperparameter optimization Meta-learning Bayesian optimization OpenML AutoML


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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	658	2015
Initializing bayesian hyperparameter optimization via meta-learning M Feurer, JT Springenberg, F Hutter Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015	232*	2015
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, 1-5, 2013	185	2013
Towards Automatically-Tuned Neural Networks H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter Proceedings of the 2016 ICML Workshop on Automatic Machine Learning 64, 58-65, 2016	91	2016
Hyperparameter Optimization M Feurer, F Hutter AutoML: Methods, Sytems, Challenges, 3-37, 2019	45	2019
OpenML Benchmarking Suites B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731v2, 2019	28*	2019
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731, 2017	27	2017
Practical Automated Machine Learning for the AutoML Challenge 2018 M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter ICML 2018 AutoML Workshop, 2018	23	2018
Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles M Feurer, B Letham, E Bakshy ICML 2018 AutoML Workshop, 2018	23*	2018
Smac v3: Algorithm configuration in python M Lindauer, K Eggensperger, M Feurer, S Falkner, A Biedenkapp, ... 2017, 2017	22	2017
Auto-sklearn: Efficient and Robust Automated Machine Learning M Feurer, A Klein, K Eggensperger, JT Springenberg, M Blum, F Hutter AutoML: Methods, Sytems, Challenges, 121-140, 2019	16	2019
Towards Further Automation in AutoML M Feurer, F Hutter ICML 2018 AutoML Workshop, 2018	8	2018
Towards Automatically-Tuned Deep Neural Networks H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ... Automated Machine Learning, 135-149, 2019	4	2019
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters M Lindauer, M Feurer, K Eggensperger, A Biedenkapp, F Hutter arXiv preprint arXiv:1908.06674, 2019	1	2019
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, J Marben, ... arXiv preprint arXiv:1908.06756, 2019	1	2019
OpenML: a networked science platform for machine learning J Vanschoren, JN van Rijn, B Bischl, G Casalicchio, M Lang, M Feurer ICML 2015 MLOSS Workshop 3, 2015	1	2015
OpenML-Python: an extensible Python API for OpenML M Feurer, JN van Rijn, A Kadra, P Gijsbers, N Mallik, S Ravi, A Müller, ... arXiv preprint arXiv:1911.02490, 2019		2019

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