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Aaron Klein
Aaron Klein
AWS Research Berlin
Verified email at amazon.com - 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 28, 2015
22272015
BOHB: Robust and efficient hyperparameter optimization at scale
S Falkner, A Klein, F Hutter
Proceedings of the 35th International Conference on Machine Learning, 2018
9002018
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
5822016
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
5202019
Bayesian optimization with robust Bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in neural information processing systems 29, 2016
4182016
Towards automatically-tuned neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter
Workshop on automatic machine learning, 58-65, 2016
2352016
Learning curve prediction with Bayesian neural networks
A Klein, S Falkner, JT Springenberg, F Hutter
International Conference on Learning Representations (ICLR) 2017, 2016
2092016
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
1842018
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
1792018
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
842017
Robo: A flexible and robust bayesian optimization framework in python
A Klein, S Falkner, N Mansur, F Hutter
NIPS 2017 Bayesian optimization workshop, 4-9, 2017
822017
Tabular benchmarks for joint architecture and hyperparameter optimization
A Klein, F Hutter
arXiv preprint arXiv:1905.04970, 2019
792019
Towards automatically-tuned deep neural networks
H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ...
Automated machine learning: Methods, systems, challenges, 135-149, 2019
762019
Fast bayesian hyperparameter optimization on large datasets
A Klein, S Falkner, S Bartels, P Hennig, F Hutter
662017
Meta-surrogate benchmarking for hyperparameter optimization
A Klein, Z Dai, F Hutter, N Lawrence, J Gonzalez
Advances in Neural Information Processing Systems 32, 2019
392019
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
332021
Towards efficient Bayesian optimization for big data
A Klein, S Bartels, S Falkner, P Hennig, F Hutter
NIPS 2015 Bayesian Optimization Workshop, 2015
302015
Model-based asynchronous hyperparameter and neural architecture search
A Klein, LC Tiao, T Lienart, C Archambeau, M Seeger
arXiv preprint arXiv:2003.10865, 2020
28*2020
Combining hyperband and bayesian optimization
S Falkner, A Klein, F Hutter
NIPS 2017 Bayesian Optimization Workshop (Dec 2017), 2017
282017
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
212015
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Articles 1–20