Aaron Klein
Aaron Klein
Amazon Research Berlin
Verified email at cs.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
7852015
Fast Bayesian optimization of machine learning hyperparameters on large datasets
A Klein, S Falkner, S Bartels, P Hennig, F Hutter
Proceedings of the 20th International Conference on Artificial Intelligence …, 2016
2212016
BOHB: Robust and efficient hyperparameter optimization at scale
S Falkner, A Klein, F Hutter
Proceedings of the 35th International Conference on Machine Learning, 2018
1852018
Bayesian optimization with robust Bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in neural information processing systems, 4134-4142, 2016
1732016
Towards automatically-tuned neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter
Workshop on Automatic Machine Learning, 58-65, 2016
1122016
Learning curve prediction with Bayesian neural networks
A Klein, S Falkner, JT Springenberg, F Hutter
International Conference on Learning Representations (ICLR) 2017, 2016
872016
Nas-bench-101: Towards reproducible neural architecture search
C Ying, A Klein, E Christiansen, E Real, K Murphy, F Hutter
International Conference on Machine Learning, 7105-7114, 2019
822019
Towards automated deep learning: Efficient joint neural architecture and hyperparameter search
A Zela, A Klein, S Falkner, F Hutter
arXiv preprint arXiv:1807.06906, 2018
462018
Uncertainty estimates and multi-hypotheses networks for optical flow
E Ilg, O Cicek, S Galesso, A Klein, O Makansi, F Hutter, T Brox
Proceedings of the European Conference on Computer Vision (ECCV), 652-667, 2018
402018
The sacred infrastructure for computational research
K Greff, A Klein, M Chovanec, F Hutter, J Schmidhuber
Proceedings of the 16th Python in Science Conference 28, 49-56, 2017
362017
Auto-sklearn: efficient and robust automated machine learning
M Feurer, A Klein, K Eggensperger, JT Springenberg, M Blum, F Hutter
Automated Machine Learning, 113-134, 2019
352019
Robo: A flexible and robust bayesian optimization framework in python
A Klein, S Falkner, N Mansur, F Hutter
NIPS 2017 Bayesian Optimization Workshop, 2017
262017
Towards efficient Bayesian optimization for big data
A Klein, S Bartels, S Falkner, P Hennig, F Hutter
NIPS 2015 Bayesian Optimization Workshop, 2015
212015
Methods for improving bayesian optimization for automl
M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter
Proceedings of the International Conference on Machine Learning, 2015
162015
Combining hyperband and bayesian optimization
S Falkner, A Klein, F Hutter
NIPS 2017 Bayesian Optimization Workshop (Dec 2017), 2017
152017
Fast bayesian hyperparameter optimization on large datasets
A Klein, S Falkner, S Bartels, P Hennig, F Hutter
Electronic Journal of Statistics 11 (2), 4945-4968, 2017
142017
Tabular benchmarks for joint architecture and hyperparameter optimization
A Klein, F Hutter
arXiv preprint arXiv:1905.04970, 2019
102019
Towards automatically-tuned deep neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ...
Automated Machine Learning, 135-149, 2019
92019
Towards reproducible neural architecture and hyperparameter search
A Klein, E Christiansen, K Murphy, F Hutter
92018
Meta-surrogate benchmarking for hyperparameter optimization
A Klein, Z Dai, F Hutter, N Lawrence, J Gonzalez
Advances in Neural Information Processing Systems, 6270-6280, 2019
82019
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