Obserwuj
Stefan Falkner
Stefan Falkner
Bosch Center for Artificial Intelligence
Zweryfikowany adres z de.bosch.com
Tytuł
Cytowane przez
Cytowane przez
Rok
BOHB: Robust and efficient hyperparameter optimization at scale
S Falkner, A Klein, F Hutter
International Conference on Machine Learning, 1437-1446, 2018
8512018
Fast bayesian optimization of machine learning hyperparameters on large datasets
A Klein, S Falkner, S Bartels, P Hennig, F Hutter
Artificial Intelligence and Statistics, 528-536, 2017
5672017
Bayesian optimization with robust Bayesian neural networks
JT Springenberg, A Klein, S Falkner, F Hutter
Advances in neural information processing systems 29, 2016
4092016
Learning curve prediction with Bayesian neural networks
A Klein, S Falkner, JT Springenberg, F Hutter
International Conference on Learning Representations, 2017
2022017
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
1772018
Auto-sklearn 2.0: The next generation
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
arXiv preprint arXiv:2007.04074 24, 2020
972020
Practical automated machine learning for the automl challenge 2018
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
International Workshop on Automatic Machine Learning at ICML, 1189-1232, 2018
862018
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
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning
M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter
80*
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
642017
Smac v3: Algorithm configuration in python
M Lindauer, K Eggensperger, M Feurer, S Falkner, A Biedenkapp, ...
URL https://github. com/automl/SMAC3, 2017
592017
Learning to Design RNA
F Runge, D Stoll, S Falkner, F Hutter
arXiv preprint arXiv:1812.11951, 2018
522018
Weak limit of the three-state quantum walk on the line
S Falkner, S Boettcher
Physical Review A 90 (1), 012307, 2014
482014
Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization
M Volpp, LP Fröhlich, K Fischer, A Doerr, S Falkner, F Hutter, C Daniel
arXiv preprint arXiv:1904.02642, 2019
472019
One-dimensional coinless quantum walks
R Portugal, S Boettcher, S Falkner
Physical Review A 91 (5), 052319, 2015
312015
Towards efficient Bayesian Optimization for Big Data
A Klein, S Bartels, S Falkner, P Hennig, F Hutter
NIPS 2015 workshop on Bayesian Optimization (BayesOpt 2015), 2015
302015
Combining hyperband and bayesian optimization
S Falkner, A Klein, F Hutter
Proceedings of the 31st Conference on Neural Information Processing Systems …, 2017
262017
Optimizing neural networks for patent classification
L Abdelgawad, P Kluegl, E Genc, S Falkner, F Hutter
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2020
242020
Relation between random walks and quantum walks
S Boettcher, S Falkner, R Portugal
Physical Review A 91 (5), 052330, 2015
242015
SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers
S Falkner, M Lindauer, F Hutter
Theory and Applications of Satisfiability Testing--SAT 2015: 18th …, 2015
222015
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