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2020 – today
- 2023
[j7]Bernd Bischl
, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer:
Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges. WIREs Data. Mining. Knowl. Discov. 13(2) (2023)- [i16]Noor H. Awad, Ayushi Sharma, Philipp Muller, Janek Thomas, Frank Hutter:
MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization. CoRR abs/2305.04502 (2023) - 2022
- [j6]Florian Pargent, Florian Pfisterer, Janek Thomas, Bernd Bischl:
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. Comput. Stat. 37(5): 2671-2692 (2022) - [c7]Lennart Schneider, Florian Pfisterer, Paul Kent, Jürgen Branke, Bernd Bischl, Janek Thomas:
Tackling Neural Architecture Search With Quality Diversity Optimization. AutoML 2022: 9/1-30 - [c6]Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl:
A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models. GECCO Companion 2022: 2136-2142 - [i15]Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl:
A Collection of Quality Diversity Optimization Problems Derived from Hyperparameter Optimization of Machine Learning Models. CoRR abs/2204.14061 (2022) - [i14]Florian Karl, Tobias Pielok, Julia Moosbauer, Florian Pfisterer, Stefan Coors, Martin Binder, Lennart Schneider, Janek Thomas, Jakob Richter, Michel Lang, Eduardo C. Garrido-Merchán, Jürgen Branke, Bernd Bischl:
Multi-Objective Hyperparameter Optimization - An Overview. CoRR abs/2206.07438 (2022) - [i13]Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren:
AMLB: an AutoML Benchmark. CoRR abs/2207.12560 (2022) - [i12]Lennart Schneider, Florian Pfisterer, Paul Kent, Jürgen Branke, Bernd Bischl, Janek Thomas:
Tackling Neural Architecture Search With Quality Diversity Optimization. CoRR abs/2208.00204 (2022) - 2021
- [j5]Ilias Gerostathopoulos, Frantisek Plásil, Christian Prehofer, Janek Thomas, Bernd Bischl:
Automated Online Experiment-Driven Adaptation-Mechanics and Cost Aspects. IEEE Access 9: 58079-58087 (2021) - [c5]Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl:
Deep Semi-supervised Learning for Time Series Classification. ICMLA 2021: 422-428 - [i11]Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl:
Deep Semi-Supervised Learning for Time Series Classification. CoRR abs/2102.03622 (2021) - [i10]Florian Pargent, Florian Pfisterer, Janek Thomas, Bernd Bischl:
Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features. CoRR abs/2104.00629 (2021) - [i9]Bernd Bischl, Martin Binder, Michel Lang, Tobias Pielok, Jakob Richter, Stefan Coors, Janek Thomas, Theresa Ullmann, Marc Becker, Anne-Laure Boulesteix, Difan Deng, Marius Lindauer:
Hyperparameter Optimization: Foundations, Algorithms, Best Practices and Open Challenges. CoRR abs/2107.05847 (2021) - 2020
- [c4]Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl:
Multi-objective hyperparameter tuning and feature selection using filter ensembles. GECCO 2020: 471-479
2010 – 2019
- 2019
- [c3]Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas:
Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning. ECML/PKDD (3) 2019: 400-415 - [i8]Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas:
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning. CoRR abs/1904.10829 (2019) - [i7]Pieter Gijsbers, Erin LeDell, Janek Thomas, Sébastien Poirier, Bernd Bischl, Joaquin Vanschoren:
An Open Source AutoML Benchmark. CoRR abs/1907.00909 (2019) - [i6]Florian Pfisterer, Stefan Coors, Janek Thomas, Bernd Bischl:
Multi-Objective Automatic Machine Learning with AutoxgboostMC. CoRR abs/1908.10796 (2019) - [i5]Florian Pfisterer, Janek Thomas, Bernd Bischl:
Towards Human Centered AutoML. CoRR abs/1911.02391 (2019) - [i4]Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl:
Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection. CoRR abs/1912.12912 (2019) - 2018
- [j4]Janek Thomas, Tobias Hepp, Andreas Mayr, Bernd Bischl:
Corrigendum to "Probing for Sparse and Fast Variable Selection with Model-Based Boosting". Comput. Math. Methods Medicine 2018: 2430438:1 (2018) - [j3]Daniel Schalk, Janek Thomas, Bernd Bischl:
compboost: Modular Framework for Component-Wise Boosting. J. Open Source Softw. 3(30): 967 (2018) - [j2]Janek Thomas, Andreas Mayr, Bernd Bischl, Matthias Schmid, Adam Smith, Benjamin Hofner:
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates. Stat. Comput. 28(3): 673-687 (2018) - [i3]Daniel Kühn, Philipp Probst, Janek Thomas, Bernd Bischl:
Automatic Exploration of Machine Learning Experiments on OpenML. CoRR abs/1806.10961 (2018) - [i2]Janek Thomas, Stefan Coors, Bernd Bischl:
Automatic Gradient Boosting. CoRR abs/1807.03873 (2018) - 2017
- [j1]Janek Thomas, Tobias Hepp, Andreas Mayr, Bernd Bischl:
Probing for Sparse and Fast Variable Selection with Model-Based Boosting. Comput. Math. Methods Medicine 2017: 1421409:1-1421409:8 (2017) - [c2]Helena Kotthaus, Jakob Richter, Andreas Lang, Janek Thomas, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer, Michel Lang:
RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization. LION 2017: 180-195 - 2016
- [c1]Michael Rietzler, Florian Geiselhart, Janek Thomas, Enrico Rukzio:
FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking. EICS 2016: 73-84 - [i1]Julia Schiffner, Bernd Bischl, Michel Lang, Jakob Richter, Zachary M. Jones, Philipp Probst, Florian Pfisterer, Mason Gallo, Dominik Kirchhoff, Tobias Kühn, Janek Thomas, Lars Kotthoff:
mlr Tutorial. CoRR abs/1609.06146 (2016)
Coauthor Index
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last updated on 2023-05-17 21:56 CEST by the dblp team
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