Janek Thomas

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Bernd BischlChair of Statistical Learning and Data Science, LMU MunichPreverjeni e-poštni naslov na stat.uni-muenchen.de
Jakob RichterTU DortmundPreverjeni e-poštni naslov na statistik.tu-dortmund.de
Michel LangTU Dortmund; LMU MunichPreverjeni e-poštni naslov na statistik.tu-dortmund.de
Stefan CoorsComputational Statistics, Ludwig-Maximilians Unversity MunichPreverjeni e-poštni naslov na campus.lmu.de
Florian Pfistererhemato GmbH, Ludwig Maximilian University of MunichPreverjeni e-poštni naslov na stat.uni-muenchen.de
Andreas MayrDept. of Medical Biometry and Statistics, University of MarburgPreverjeni e-poštni naslov na uni-marburg.de
Pieter GijsbersEindhoven University of TechnologyPreverjeni e-poštni naslov na tue.nl
Joaquin VanschorenEindhoven University of TechnologyPreverjeni e-poštni naslov na tue.nl
Daniel HornStatistical Methods for Big Data, TU DortmundPreverjeni e-poštni naslov na tu-dortmund.de
Julia MoosbauerPhD Student, Ludwig-Maximilians-University MunichPreverjeni e-poštni naslov na stat.uni-muenchen.de
Jakob BossekPaderborn UniversityPreverjeni e-poštni naslov na uni-paderborn.de
Florian PargentPsychological Methods and Assessment, LMU MunichPreverjeni e-poštni naslov na psy.lmu.de
Jann GoschenhoferPhD Candidate, LMUPreverjeni e-poštni naslov na stat.uni-muenchen.de
Tobias HeppDepartment of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-Universität Erlangen-NürnbergPreverjeni e-poštni naslov na fau.de
Adam D. SmithU.S. Motus Director, American Bird ConservancyPreverjeni e-poštni naslov na abcbirds.org
Franz MJ PfisterData Science, LMUPreverjeni e-poštni naslov na campus.lmu.de
Kamer Ali YUKSELHead of AI Lab @ aiXplainPreverjeni e-poštni naslov na badehotels.com
Philipp ProbstPreverjeni e-poštni naslov na digital-ratio.de
Enrico RukzioUlm UniversityPreverjeni e-poštni naslov na uni-ulm.de
Michael RietzlerUlm UniversityPreverjeni e-poštni naslov na uni-ulm.de

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Janek Thomas

Ludwig-Maximilians-University Munich

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

Artificial Intelligence Machine Learning AutoML Statistics Optimization


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 13 (2 …, 2023	618	2023
An Open Source AutoML Benchmark P Gijsbers, E LeDell, J Thomas, S Poirier, B Bischl, J Vanschoren ICML AutoML Workshop, 2019	322	2019
mlrMBO: A modular framework for model-based optimization of expensive black-box functions B Bischl, J Richter, J Bossek, D Horn, J Thomas, M Lang arXiv preprint arXiv:1703.03373, 2017	222*	2017
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features F Pargent, F Pfisterer, J Thomas, B Bischl Computational Statistics 37 (5), 2671-2692, 2022	153*	2022
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates J Thomas, A Mayr, B Bischl, M Schmid, A Smith, B Hofner Statistics and Computing 28 (3), 673-687, 2018	88	2018
Amlb: an automl benchmark P Gijsbers, MLP Bueno, S Coors, E LeDell, S Poirier, J Thomas, B Bischl, ... Journal of Machine Learning Research 25 (101), 1-65, 2024	84	2024
Multi-objective hyperparameter optimization in machine learning—An overview F Karl, T Pielok, J Moosbauer, F Pfisterer, S Coors, M Binder, L Schneider, ... ACM Transactions on Evolutionary Learning and Optimization 3 (4), 1-50, 2023	72	2023
Multi-objective hyperparameter tuning and feature selection using filter ensembles M Binder, J Moosbauer, J Thomas, B Bischl Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 471-479, 2020	66	2020
Automatic Gradient Boosting J Thomas, S Coors, B Bischl ICML AutoML Workshop, 2018	36	2018
Probing for sparse and fast variable selection with model-based boosting J Thomas, T Hepp, A Mayr, B Bischl Computational and Mathematical Methods in Medicine 2017, 8 pages, 2017	35	2017
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning J Goschenhofer, FMJ Pfister, KA Yuksel, B Bischl, U Fietzek, J Thomas Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019	28	2019
Deep semi-supervised learning for time-series classification J Goschenhofer Deep Learning Applications, Volume 4, 361-384, 2022	22	2022
Multi-objective automatic machine learning with autoxgboostmc F Pfisterer, S Coors, J Thomas, B Bischl arXiv preprint arXiv:1908.10796, 2019	20	2019
FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking M Rietzler, F Geiselhart, J Thomas, E Rukzio Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive …, 2016	19	2016
Towards human centered AutoML F Pfisterer, J Thomas, B Bischl arXiv preprint arXiv:1911.02391, 2019	17	2019
Automatic exploration of machine learning experiments on openml D Kühn, P Probst, J Thomas, B Bischl arXiv preprint arXiv:1806.10961, 2018	17	2018
RAMBO: Resource-aware model-based optimization with scheduling for heterogeneous runtimes and a comparison with asynchronous model-based optimization H Kotthaus, J Richter, A Lang, J Thomas, B Bischl, P Marwedel, ... Learning and Intelligent Optimization: 11th International Conference, LION …, 2017	17	2017
Hyperparameter optimization: Foundations, algorithms, best practices and open challenges. arXiv B Bischl, M Binder, M Lang, T Pielok, J Richter, S Coors, J Thomas, ... arXiv preprint arXiv:2107.05847, 2021	12	2021
Meta learning for defaults: Symbolic defaults JN van Rijn, F Pfisterer, J Thomas, A Muller, B Bischl, J Vanschoren Neural Information Processing Workshop on Meta-Learning, 2018	12	2018
Structured verification of machine learning models in industrial settings SR Kaminwar, J Goschenhofer, J Thomas, I Thon, B Bischl Big Data 11 (3), 181-198, 2023	11	2023

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