Matthias Feurer
Matthias Feurer
Machine Learning group, University of Freiburg
Verified email at informatik.uni-freiburg.de - Homepage
Title
Cited by
Cited by
Year
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
1409*2015
Hyperparameter Optimization
M Feurer, F Hutter
AutoML: Methods, Sytems, Challenges, 3-37, 2019
3762019
Initializing bayesian hyperparameter optimization via meta-learning
M Feurer, J Springenberg, F Hutter
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
375*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
2962013
Towards Automatically-Tuned Deep Neural Networks
H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ...
Automated Machine Learning, 135-149, 2019
215*2019
Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles
M Feurer, B Letham, E Bakshy
ICML 2018 AutoML Workshop, 2018
63*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
622018
OpenML Benchmarking Suites
B Bischl, G Casalicchio, M Feurer, F Hutter, M Lang, RG Mantovani, ...
arXiv preprint arXiv:1708.03731v2, 2019
61*2019
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ...
arXiv preprint arXiv:2109.09831, 2021
49*2021
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
33*2021
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
232021
Towards Further Automation in AutoML
M Feurer, F Hutter
ICML 2018 AutoML Workshop, 2018
212018
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
162019
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
62019
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
32015
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
12021
Squirrel: A Switching Hyperparameter Optimizer
N Awad, G Shala, D Deng, N Mallik, M Feurer, K Eggensperger, ...
arXiv preprint arXiv:2012.08180, 2020
12020
The system can't perform the operation now. Try again later.
Articles 1–17