Janek Thomas

According to our database, Janek Thomas authored at least 27 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Multi-Objective Hyperparameter Optimization in Machine Learning - An Overview.

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

ACM Trans. Evol. Learn. Optim., December, 2023

Structured Verification of Machine Learning Models in Industrial Settings.

Sai Rahul Kaminwar, Jann Goschenhofer, Janek Thomas, Ingo Thon, Bernd Bischl

Big Data, June, 2023

Hyperparameter optimization: Foundations, algorithms, best practices, and open challenges.

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

WIREs Data. Mining. Knowl. Discov., 2023

MO-DEHB: Evolutionary-based Hyperband for Multi-Objective Optimization.

Noor H. Awad, Ayushi Sharma, Philipp Muller, Janek Thomas, Frank Hutter

CoRR, 2023

Multi-Objective Optimization of Performance and Interpretability of Tabular Supervised Machine Learning Models.

Lennart Schneider, Bernd Bischl, Janek Thomas

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

2022

Regularized target encoding outperforms traditional methods in supervised machine learning with high cardinality features.

Florian Pargent, Florian Pfisterer, Janek Thomas, Bernd Bischl

Comput. Stat., 2022

AMLB: an AutoML Benchmark.

Pieter Gijsbers, Marcos L. P. Bueno, Stefan Coors, Erin LeDell, Sébastien Poirier, Janek Thomas, Bernd Bischl, Joaquin Vanschoren

CoRR, 2022

Multi-Objective Hyperparameter Optimization - An Overview.

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

CoRR, 2022

A collection of quality diversity optimization problems derived from hyperparameter optimization of machine learning models.

Lennart Schneider, Florian Pfisterer, Janek Thomas, Bernd Bischl

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Tackling Neural Architecture Search With Quality Diversity Optimization.

Lennart Schneider, Florian Pfisterer, Paul Kent, Jürgen Branke, Bernd Bischl, Janek Thomas

Proceedings of the International Conference on Automated Machine Learning, 2022

2021

Automated Online Experiment-Driven Adaptation-Mechanics and Cost Aspects.

Ilias Gerostathopoulos, Frantisek Plásil, Christian Prehofer, Janek Thomas, Bernd Bischl

IEEE Access, 2021

Deep Semi-supervised Learning for Time Series Classification.

Jann Goschenhofer, Rasmus Hvingelby, David Rügamer, Janek Thomas, Moritz Wagner, Bernd Bischl

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Multi-objective hyperparameter tuning and feature selection using filter ensembles.

Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl

Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020

2019

Model-Agnostic Approaches to Multi-Objective Simultaneous Hyperparameter Tuning and Feature Selection.

Martin Binder, Julia Moosbauer, Janek Thomas, Bernd Bischl

CoRR, 2019

Towards Human Centered AutoML.

Florian Pfisterer, Janek Thomas, Bernd Bischl

CoRR, 2019

Multi-Objective Automatic Machine Learning with AutoxgboostMC.

Florian Pfisterer, Stefan Coors, Janek Thomas, Bernd Bischl

CoRR, 2019

An Open Source AutoML Benchmark.

Pieter Gijsbers, Erin LeDell, Janek Thomas, Sébastien Poirier, Bernd Bischl, Joaquin Vanschoren

CoRR, 2019

Wearable-Based Parkinson's Disease Severity Monitoring Using Deep Learning.

Jann Goschenhofer, Franz Michael Josef Pfister, Kamer Ali Yuksel, Bernd Bischl, Urban Fietzek, Janek Thomas

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

2018

Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.

Janek Thomas, Andreas Mayr, Bernd Bischl, Matthias Schmid, Adam Smith, Benjamin Hofner

Stat. Comput., 2018

compboost: Modular Framework for Component-Wise Boosting.

Daniel Schalk, Janek Thomas, Bernd Bischl

J. Open Source Softw., 2018

Automatic Gradient Boosting.

Janek Thomas, Stefan Coors, Bernd Bischl

CoRR, 2018

Automatic Exploration of Machine Learning Experiments on OpenML.

Daniel Kühn, Philipp Probst, Janek Thomas, Bernd Bischl

CoRR, 2018

Corrigendum to "Probing for Sparse and Fast Variable Selection with Model-Based Boosting".

Janek Thomas, Tobias Hepp, Andreas Mayr, Bernd Bischl

Comput. Math. Methods Medicine, 2018

2017

Probing for Sparse and Fast Variable Selection with Model-Based Boosting.

Janek Thomas, Tobias Hepp, Andreas Mayr, Bernd Bischl

Comput. Math. Methods Medicine, 2017

RAMBO: Resource-Aware Model-Based Optimization with Scheduling for Heterogeneous Runtimes and a Comparison with Asynchronous Model-Based Optimization.

Helena Kotthaus, Jakob Richter, Andreas Lang, Janek Thomas, Bernd Bischl, Peter Marwedel, Jörg Rahnenführer, Michel Lang

Proceedings of the Learning and Intelligent Optimization - 11th International Conference, 2017

2016

mlr Tutorial.

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

CoRR, 2016

FusionKit: a generic toolkit for skeleton, marker and rigid-body tracking.

Michael Rietzler, Florian Geiselhart, Janek Thomas, Enrico Rukzio

Proceedings of the 8th ACM SIGCHI Symposium on Engineering Interactive Computing Systems, 2016