Matthias Feurer
Matthias Feurer
Machine Learning group, University of Freiburg
Verified email at informatik.uni-freiburg.de - Homepage
TitleCited byYear
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
5422015
Initializing bayesian hyperparameter optimization via meta-learning
M Feurer, JT Springenberg, F Hutter
Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015
206*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
1642013
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
742016
OpenML benchmarking suites and the OpenML100
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731, 2017
232017
Hyperparameter Optimization
M Feurer, F Hutter
AutoML: Methods, Sytems, Challenges, 3-37, 2019
212019
Practical Automated Machine Learning for the AutoML Challenge 2018
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
ICML 2018 AutoML Workshop, 2018
192018
Smac v3: Algorithm configuration in python
M Lindauer, K Eggensperger, M Feurer, S Falkner, A Biedenkapp, ...
192017
Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles
M Feurer, B Letham, E Bakshy
ICML 2018 AutoML Workshop, 2018
16*2018
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
72019
Towards Further Automation in AutoML
M Feurer, F Hutter
ICML 2018 AutoML Workshop, 2018
52018
Towards Automatically-Tuned Deep Neural Networks
H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ...
Automated Machine Learning, 135-149, 2019
32019
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
12015
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
OpenML Benchmarking Suites
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731v2, 2019
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
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
2019
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