Matthias Feurer

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Frank HutterELLIS Institute Tübingen & Professor, University of Freiburg, GermanyPreverjeni e-poštni naslov na cs.uni-freiburg.de
Katharina EggenspergerEarly Career Group Leader "AutoML for Science" | University of TübingenPreverjeni e-poštni naslov na uni-tuebingen.de
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchPreverjeni e-poštni naslov na ai.uni-hannover.de
Aaron KleinScaDS.AIPreverjeni e-poštni naslov na amazon.com
Manuel BlumUniversity of FreiburgPreverjeni e-poštni naslov na informatik.uni-freiburg.de
Bernd BischlChair of Statistical Learning and Data Science, LMU MunichPreverjeni e-poštni naslov na stat.uni-muenchen.de
André BiedenkappUniversity of FreiburgPreverjeni e-poštni naslov na cs.uni-freiburg.de
Stefan FalknerBosch Corporate ResearchPreverjeni e-poštni naslov na de.bosch.com
Joaquin VanschorenEindhoven University of TechnologyPreverjeni e-poštni naslov na tue.nl
Giuseppe CasalicchioSenior Lecturer and Researcher, LMU Munich, Munich Center for Machine LearningPreverjeni e-poštni naslov na campus.lmu.de
Jan N. van RijnLeiden UniversityPreverjeni e-poštni naslov na liacs.leidenuniv.nl
Difan DengLeibniz Universität HannoverPreverjeni e-poštni naslov na tnt.uni-hannover.de
Neeratyoy MallikPhD student, AutoML FreiburgPreverjeni e-poštni naslov na cs.uni-freiburg.de
Eytan BakshyResearch Director, MetaPreverjeni e-poštni naslov na fb.com
Pieter GijsbersEindhoven University of TechnologyPreverjeni e-poštni naslov na tue.nl
Rafael Gomes MantovaniFederal Technology University - Paraná, campus of ApucaranaPreverjeni e-poštni naslov na utfpr.edu.br
Michel LangTU Dortmund; LMU MunichPreverjeni e-poštni naslov na statistik.tu-dortmund.de
Noor AwadPostdoctoral Research Fellow, University of FreiburgPreverjeni e-poštni naslov na cs.uni-freiburg.de
Kevin Leyton-BrownProfessor, Computer Science, University of British Columbia; Canada CIFAR AI ChairPreverjeni e-poštni naslov na cs.ubc.ca
James BergstraPrincipal Engineer, Ocado TechnologyPreverjeni e-poštni naslov na ocado.com

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Matthias Feurer

LMU Munich

Preverjeni e-poštni naslov na stat.uni-muenchen.de - Domača stran

Hyperparameter optimization Meta-learning Bayesian optimization OpenML AutoML


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, 2962-2970, 2015	2998	2015
Hyperparameter Optimization M Feurer, F Hutter AutoML: Methods, Sytems, Challenges, 3-37, 2019	1885	2019
Initializing bayesian hyperparameter optimization via meta-learning M Feurer, J Springenberg, F Hutter Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015	674*	2015
Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter Journal of Machine Learning Research 23 (261), 1-61, 2022	660*	2022
Towards an empirical foundation for assessing bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... NIPS workshop on Bayesian Optimization in Theory and Practice, 1-5, 2013	479	2013
SMAC3: A versatile Bayesian optimization package for hyperparameter optimization M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ... Journal of Machine Learning Research 23 (54), 1-9, 2022	458*	2022
Towards Automatically-Tuned Deep Neural Networks H Mendoza, A Klein, M Feurer, JT Springenberg, M Urban, M Burkart, ... Automated Machine Learning, 135-149, 2019	378*	2019
OpenML Benchmarking Suites B Bischl, G Casalicchio, M Feurer, P Gijsbers, F Hutter, M Lang, ... Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021	244*	2021
Practical Transfer Learning for Bayesian Optimization M Feurer, B Letham, F Hutter, E Bakshy arXiv:1802.02219v3, 2022	178*	2022
OpenML-Python: an extensible Python API for OpenML M Feurer, JN van Rijn, A Kadra, P Gijsbers, N Mallik, S Ravi, A Müller, ... Journal of Machine Learning Research 22 (100), 1-5, 2021	111	2021
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, ... Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021	104	2021
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, J Marben, ... arXiv preprint arXiv:1908.06756, 2019	53	2019
PFNs4BO: In-Context Learning for Bayesian Optimization S Müller, M Feurer, N Hollmann, F Hutter 40th International Conference on Machine Learning, 2023	39	2023
OpenML-CTR23–A curated tabular regression benchmarking suite SF Fischer, M Feurer, B Bischl AutoML Conference 2023 (Workshop), 2023	26	2023
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters M Lindauer, M Feurer, K Eggensperger, A Biedenkapp, F Hutter arXiv preprint arXiv:1908.06674, 2019	24	2019
Can fairness be automated? guidelines and opportunities for fairness-aware automl H Weerts, F Pfisterer, M Feurer, K Eggensperger, E Bergman, N Awad, ... Journal of Artificial Intelligence Research 79, 639-677, 2024	21	2024
Position: Why We Must Rethink Empirical Research in Machine Learning M Herrmann, FJD Lange, K Eggensperger, G Casalicchio, M Wever, ... Forty-first International Conference on Machine Learning, 2024	9*	2024
Mind the Gap: Measuring Generalization Performance Across Multiple Objectives M Feurer, K Eggensperger, E Bergman, F Pfisterer, B Bischl, F Hutter International Symposium on Intelligent Data Analysis, 130-142, 2023	7	2023
Position: A Call to Action for a Human-Centered AutoML Paradigm M Lindauer, F Karl, A Klier, J Moosbauer, A Tornede, A Mueller, F Hutter, ... Accepted at ICML 2024, 2024	6	2024
Squirrel: A Switching Hyperparameter Optimizer N Awad, G Shala, D Deng, N Mallik, M Feurer, K Eggensperger, ... arXiv preprint arXiv:2012.08180, 2020	6	2020

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