Matthias Feurer

Orcid: 0000-0001-9611-8588

According to our database1, Matthias Feurer authored at least 29 papers between 2001 and 2024.

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Bibliography

2024
Can Fairness be Automated? Guidelines and Opportunities for Fairness-aware AutoML.
J. Artif. Intell. Res., 2024

Interpretable Machine Learning for TabPFN.
CoRR, 2024

2023
PFNs Are Flexible Models for Real-World Bayesian Optimization.
CoRR, 2023

Mind the Gap: Measuring Generalization Performance Across Multiple Objectives.
Proceedings of the Advances in Intelligent Data Analysis XXI, 2023

PFNs4BO: In-Context Learning for Bayesian Optimization.
Proceedings of the International Conference on Machine Learning, 2023

2022
Robust and efficient automated machine learning: systems, infrastructure and advances in hyperparameter optimization.
PhD thesis, 2022

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.
J. Mach. Learn. Res., 2022

Auto-Sklearn 2.0: Hands-free AutoML via Meta-Learning.
J. Mach. Learn. Res., 2022

2021
OpenML-Python: an extensible Python API for OpenML.
J. Mach. Learn. Res., 2021

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization.
CoRR, 2021

HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

OpenML Benchmarking Suites.
Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

2020
Squirrel: A Switching Hyperparameter Optimizer.
CoRR, 2020

Auto-Sklearn 2.0: The Next Generation.
CoRR, 2020

System Architectures for Cyber-Physical Production Systems enabling Self-X and Autonomy.
Proceedings of the 25th IEEE International Conference on Emerging Technologies and Factory Automation, 2020

2019
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters.
CoRR, 2019

Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters.
CoRR, 2019

Towards Automatically-Tuned Deep Neural Networks.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Auto-sklearn: Efficient and Robust Automated Machine Learning.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

Hyperparameter Optimization.
Proceedings of the Automated Machine Learning - Methods, Systems, Challenges, 2019

2018
Scalable Meta-Learning for Bayesian Optimization.
CoRR, 2018

2017
OpenML Benchmarking Suites and the OpenML100.
CoRR, 2017

2016
Towards Automatically-Tuned Neural Networks.
Proceedings of the 2016 Workshop on Automatic Machine Learning, 2016

2015
Efficient and Robust Automated Machine Learning.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Initializing Bayesian Hyperparameter Optimization via Meta-Learning.
Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015

2014
Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters.
Proceedings of the International Workshop on Meta-learning and Algorithm Selection co-located with 21st European Conference on Artificial Intelligence, 2014

2004
Tailor tools for interactive design of clothing in virtual environments.
Proceedings of the ACM Symposium on Virtual Reality Software and Technology, 2004

2003
Interactive Cloth Simulation in Virtual Environments.
Proceedings of the IEEE Virtual Reality Conference 2003 (VR 2003), 2003

2001
Exploring the past: a toolset for visualization of historical events in virtual environments.
Proceedings of the ACM Symposium on Virtual Reality Software and Technology, 2001


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