Matthias Feurer

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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 KleinAWS 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
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
André BiedenkappPhD candidate, University of FreiburgVerified email at cs.uni-freiburg.de
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairVerified 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 BischlChair of Statistical Learning and Data Science, LMU MunichVerified email at stat.uni-muenchen.de
Michel LangTU Dortmund; LMU MunichVerified email at statistik.tu-dortmund.de
Giuseppe CasalicchioPostdoctoral Researcher, LMU Munich, Munich Center for Machine LearningVerified email at campus.lmu.de
Eytan BakshyResearch Director, FacebookVerified email at fb.com
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br
Neeratyoy MallikUniversity of FreiburgVerified email at cs.uni-freiburg.de

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	1231*	2015
Initializing bayesian hyperparameter optimization via meta-learning M Feurer, J Springenberg, F Hutter Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	337*	2015
Hyperparameter Optimization M Feurer, F Hutter AutoML: Methods, Sytems, Challenges, 3-37, 2019	280	2019
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	270	2013
Towards Automatically-Tuned Deep Neural Networks H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ... Automated Machine Learning, 135-149, 2019	193*	2019
Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles M Feurer, B Letham, E Bakshy ICML 2018 AutoML Workshop, 2018	57*	2018
Practical Automated Machine Learning for the AutoML Challenge 2018 M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter ICML 2018 AutoML Workshop, 2018	56	2018
OpenML Benchmarking Suites B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731v2, 2019	52*	2019
Smac v3: Algorithm configuration in python M Lindauer, K Eggensperger, M Feurer, S Falkner, A Biedenkapp, ... URL https://github. com/automl/SMAC3, 2017	43	2017
OpenML benchmarking suites and the OpenML100 B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731, 2017	41	2017
Auto-Sklearn 2.0: The Next Generation M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter arXiv preprint arXiv:2007.04074, 2020	20	2020
Towards Further Automation in AutoML M Feurer, F Hutter ICML 2018 AutoML Workshop, 2018	18	2018
OpenML-Python: an extensible Python API for OpenML M Feurer, JN van Rijn, A Kadra, P Gijsbers, N Mallik, S Ravi, A Müller, ... Journal of Machine Learning Research 22 (100), 1-5, 2021	17	2021
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	10	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	3	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	2	2015
Squirrel: A Switching Hyperparameter Optimizer N Awad, G Shala, D Deng, N Mallik, M Feurer, K Eggensperger, ... arXiv preprint arXiv:2012.08180, 2020		2020

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