עקוב אחר
Frank Hutter
Frank Hutter
ELLIS Institute Tübingen & Professor, University of Freiburg, Germany
כתובת אימייל מאומתת בדומיין cs.uni-freiburg.de - דף הבית
כותרת
צוטט על ידי
צוטט על ידי
שנה
Decoupled weight decay regularization‏
I Loshchilov, F Hutter‏
ICLR 2019, 2017‏
247512017
Sgdr: Stochastic gradient descent with warm restarts‏
I Loshchilov, F Hutter‏
ICLR 2017, 2016‏
94132016
Neural architecture search: A survey‏
T Elsken, JH Metzen, F Hutter‏
Journal of Machine Learning Research 20 (55), 1-21, 2019‏
35002019
Sequential model-based optimization for general algorithm configuration‏
F Hutter, HH Hoos, K Leyton-Brown‏
Learning and Intelligent Optimization: 5th International Conference, LION 5 …, 2011‏
33772011
Deep learning with convolutional neural networks for EEG decoding and visualization‏
RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ...‏
Human brain mapping 38 (11), 5391-5420, 2017‏
29782017
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
29692015
Automated machine learning: methods, systems, challenges‏
F Hutter, L Kotthoff, J Vanschoren‏
Springer Nature, 2019‏
22082019
Auto-WEKA: Combined selection and hyperparameter optimization of classification algorithms‏
C Thornton, F Hutter, HH Hoos, K Leyton-Brown‏
Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013‏
21162013
Hyperparameter optimization‏
M Feurer, F Hutter‏
Automated machine learning: Methods, systems, challenges, 3-33, 2019‏
17482019
BOHB: Robust and efficient hyperparameter optimization at scale‏
S Falkner, A Klein, F Hutter‏
International conference on machine learning, 1437-1446, 2018‏
13482018
ParamILS: an automatic algorithm configuration framework‏
F Hutter, HH Hoos, K Leyton-Brown, T Stützle‏
Journal of artificial intelligence research 36, 267-306, 2009‏
12912009
SATzilla: portfolio-based algorithm selection for SAT‏
L Xu, F Hutter, HH Hoos, K Leyton-Brown‏
Journal of artificial intelligence research 32, 565-606, 2008‏
11792008
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA‏
L Kotthoff, C Thornton, HH Hoos, F Hutter, K Leyton-Brown‏
Journal of Machine Learning Research 18 (25), 1-5, 2017‏
9892017
Bayesian optimization in a billion dimensions via random embeddings‏
Z Wang, F Hutter, M Zoghi, D Matheson, N De Feitas‏
Journal of Artificial Intelligence Research 55, 361-387, 2016‏
8702016
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
8332019
Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves‏
T Domhan, JT Springenberg, F Hutter‏
Twenty-fourth international joint conference on artificial intelligence, 2015‏
8132015
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
7462017
A downsampled variant of imagenet as an alternative to the cifar datasets‏
P Chrabaszcz, I Loshchilov, F Hutter‏
arXiv preprint arXiv:1707.08819, 2017‏
6982017
Efficient multi-objective neural architecture search via lamarckian evolution‏
T Elsken, JH Metzen, F Hutter‏
arXiv preprint arXiv:1804.09081, 2018‏
6562018
An efficient approach for assessing hyperparameter importance‏
F Hutter, H Hoos, K Leyton-Brown‏
International conference on machine learning, 754-762, 2014‏
6402014
המערכת אינה יכולה לבצע את הפעולה כעת. נסה שוב מאוחר יותר.
מאמרים 1–20