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
Marius LindauerLeibniz University Hannover (Germany)Verified email at tnt.uni-hannover.de
Manuel BlumUniversity of FreiburgVerified email at informatik.uni-freiburg.de
Stefan FalknerBosch Center for Artificial IntelligenceVerified email at de.bosch.com
André BiedenkappPhD candidate, University of FreiburgVerified email at cs.uni-freiburg.de
Jan N. van RijnLeiden UniversityVerified email at liacs.leidenuniv.nl
Joaquin VanschorenEindhoven University of TechnologyVerified email at tue.nl
Eytan BakshyResearch Director, MetaVerified email at fb.com
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 HoosRWTH Aachen University, Germany • Leiden University, Netherlands • University of British ColumbiaVerified email at cs.rwth-aachen.de
Neeratyoy MallikPhD student, AutoML FreiburgVerified email at cs.uni-freiburg.de
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
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaVerified email at utfpr.edu.br

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	1673	2015
Hyperparameter Optimization M Feurer, F Hutter AutoML: Methods, Sytems, Challenges, 3-37, 2019	541	2019
Initializing bayesian hyperparameter optimization via meta-learning M Feurer, J Springenberg, F Hutter Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	429*	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	332	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	247*	2019
Practical Transfer Learning for Bayesian Optimization M Feurer, B Letham, F Hutter, E Bakshy arXiv:1802.02219v3, 2022	81*	2022
OpenML Benchmarking Suites B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ... arXiv preprint arXiv:1708.03731v2, 2019	71	2019
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter	70*	2021
Practical Automated Machine Learning for the AutoML Challenge 2018 M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter ICML 2018 AutoML Workshop, 2018	67	2018
SMAC3: A versatile Bayesian optimization package for hyperparameter optimization M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ... Journal of Machine Learning Research 23 (54), 1-9, 2022	62*	2022
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	35	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	24	2019
Towards Further Automation in AutoML M Feurer, F Hutter ICML 2018 AutoML Workshop, 2018	23	2018
HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO K Eggensperger, P Müller, N Mallik, M Feurer, R Sass, A Klein, N Awad, ... arXiv preprint arXiv:2109.06716, 2021	8	2021
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	7	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	3	2015
Squirrel: A Switching Hyperparameter Optimizer N Awad, G Shala, D Deng, N Mallik, M Feurer, K Eggensperger, ... arXiv preprint arXiv:2012.08180, 2020	2	2020

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