Aaron Klein

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Soavtorji

Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyPreverjeni e-poštni naslov na cs.uni-freiburg.de
Stefan FalknerBosch Corporate ResearchPreverjeni e-poštni naslov na de.bosch.com
Matthias FeurerLMU MunichPreverjeni e-poštni naslov na stat.uni-muenchen.de
Katharina EggenspergerEarly Career Group Leader "AutoML for Science" | University of TübingenPreverjeni e-poštni naslov na uni-tuebingen.de
Cédric ArchambeauDirector of AI at Helsing. Ex Principal Applied Scientist at AWS.Preverjeni e-poštni naslov na helsing.ai
Manuel BlumUniversity of FreiburgPreverjeni e-poštni naslov na informatik.uni-freiburg.de
Matthias SeegerPrincipal Applied Scientist, Amazon, BerlinPreverjeni e-poštni naslov na amazon.de
Philipp HennigUniversity of TübingenPreverjeni e-poštni naslov na uni-tuebingen.de
Thomas BroxUniversity of FreiburgPreverjeni e-poštni naslov na cs.uni-freiburg.de
Eddy IlgProfessor at the University of Technology NurembergPreverjeni e-poštni naslov na cs.uni-saarland.de
Özgün ÇİÇEKRobert Bosch GmbH, Corporate ResearchPreverjeni e-poštni naslov na de.bosch.com
Arber ZelaPhD student, University of FreiburgPreverjeni e-poštni naslov na cs.uni-freiburg.de
David SalinasUniversity of FreiburgPreverjeni e-poštni naslov na ens-lyon.org
Jacek Golebiowskidistil labsPreverjeni e-poštni naslov na distillabs.ai
Muhammad Numair MansurAmazon Web ServicesPreverjeni e-poštni naslov na amazon.com
Rhea Sanjay SukthankerGraduate StudentPreverjeni e-poštni naslov na cs.uni-freiburg.de
Jost Tobias SpringenbergGoogle DeepMind

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Aaron Klein

ScaDS.AI

Preverjeni e-poštni naslov na amazon.com - Domača stran

AutoML Neural Architecture Search Bayesian Optimization Deep Learning


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
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	3091	2015
BOHB: Robust and efficient hyperparameter optimization at scale S Falkner, A Klein, F Hutter Proceedings of the 35th International Conference on Machine Learning, 2018	1411	2018
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	874	2019
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	758	2016
Bayesian optimization with robust Bayesian neural networks JT Springenberg, A Klein, S Falkner, F Hutter Advances in neural information processing systems 29, 2016	571	2016
Towards automatically-tuned neural networks H Mendoza, A Klein, M Feurer, JT Springenberg, F Hutter Workshop on automatic machine learning, 58-65, 2016	380	2016
Learning curve prediction with Bayesian neural networks A Klein, S Falkner, JT Springenberg, F Hutter International Conference on Learning Representations (ICLR) 2017, 2016	289	2016
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	255	2018
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	238	2018
Tabular benchmarks for joint architecture and hyperparameter optimization A Klein, F Hutter arXiv preprint arXiv:1905.04970, 2019	117	2019
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	112	2017
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	104	2021
The Sacred Infrastructure for Computational Research. K Greff, A Klein, M Chovanec, F Hutter, J Schmidhuber SciPy 17, 49-56, 2017	104	2017
Fast bayesian hyperparameter optimization on large datasets A Klein, S Falkner, S Bartels, P Hennig, F Hutter	85	2017
Automatic Termination for Hyperparameter Optimization A Makarova, H Shen, V Perrone, A Klein, JB Faddoul, A Krause, ... First Conference on Automated Machine Learning (Main Track), 2021	60*	2021
Model-based asynchronous hyperparameter and neural architecture search A Klein, LC Tiao, T Lienart, C Archambeau, M Seeger arXiv preprint arXiv:2003.10865, 2020	54	2020
Meta-surrogate benchmarking for hyperparameter optimization A Klein, Z Dai, F Hutter, N Lawrence, J Gonzalez Advances in Neural Information Processing Systems 32, 2019	49	2019
Syne tune: A library for large scale hyperparameter tuning and reproducible research D Salinas, M Seeger, A Klein, V Perrone, M Wistuba, C Archambeau International Conference on Automated Machine Learning, 16/1-23, 2022	47	2022
BORE: Bayesian optimization by density-ratio estimation LC Tiao, A Klein, MW Seeger, EV Bonilla, C Archambeau, F Ramos International Conference on Machine Learning, 10289-10300, 2021	42	2021
Combining hyperband and bayesian optimization S Falkner, A Klein, F Hutter NIPS 2017 Bayesian Optimization Workshop (Dec 2017), 2017	36	2017

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