Uni-Logo

2020

  • Eggensperger, Katharina and Haase, Kai and Müller, Philipp and Lindauer, Marius and Hutter, Frank (arXiv)(bib)
    Neural Model-based Optimization with Right-Censored Observations
    In: arXiv:2009:13828 [cs.AI] (2020)
  • Feurer, Matthias and Eggensperger, Katharina and Falkner, Stefan and Lindauer, Marius and Hutter, Frank (arXiv)(bib)
    Auto-sklearn 2.0: The Next Generation
    In: arXiv:2007:04074 [cs.LG] (2020)

2019

  • Lindauer, Marius and Feurer, Matthias and Eggensperger, Katharina and Biedenkapp, André and Hutter, Frank (arXiv)(slides)(bib)
    Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
    In: IJCAI 2019 DSO Workshop
  • Lindauer, Marius and Eggensperger, Katharina and Feurer, Matthias and Biedenkapp, André and Marben, Joshua and Müller, Philipp and Hutter, Frank (arXiv)(bib)
    BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters
    In: arXiv:1908.06756 [cs.LG] (2019)
    (Code)(Project Page)
  • Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina and Springenberg, Jost and Blum, Manuel and Hutter, Frank (arXiv)(published)(bib)
    Auto-sklearn: Efficient and Robust Automated Machine Learning
    In: AutoML: Methods, Systems, Challenges
  • Eggensperger, Katharina and Lindauer, Marius and Hutter, Frank (arXiv)(published)(bib)
    Pitfalls and Best Practices in Algorithm Configuration
    In: Journal of Artificial Intelligence Research (JAIR) 64 (2019): 861--893

2018

  • Eggensperger, Katharina and Lindauer, Marius and Hutter, Frank (arXiv)(published)(poster)(slides)(bib)
    Neural Networks for Predicting Algorithm Runtime Distributions
    In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI’18)
  • Feurer, Matthias and Eggensperger, Katharina and Falkner, Stefan and Lindauer, Marius and Hutter, Frank (pdf)(bib)
    Practical Automated Machine Learning for the AutoML Challenge 2018
    In: ICML 2018 AutoML Workshop
  • Eggensperger, Katharina and Lindauer, Marius and Hoos, Holger H. and Hutter, Frank and Leyton-Brown, Kevin (arXiv)(published)(bib)
    Efficient Benchmarking of Algorithm Configurators via Model-Based Surrogates
    In: Machine Learning 107 (2018): 15-41

2017

  • Martinez-Cantin, Ruben and Tee, Kevin and McCourt, Mike and Eggensperger, Katharina (pdf)(supplementary)(poster)(bib)
    Filtering Outliers in Bayesian Optimization
    In: NeuriPS workshop on Bayesian Optimization (BayesOpt'17)
  • Biedenkapp, André and Lindauer, Marius and Eggensperger, Katharina and Fawcett, Chris and Hoos, Holger H. and Hutter, Frank (pdf)(poster)(bib)
    Efficient Parameter Importance Analysis via Ablation with Surrogates
    In: Proceedings of the Thirty-First Conference on Artificial Intelligence (AAAI'17)
    (Code)(Project Page)
  • Schirrmeister, Robin and Springenberg, Jost Tobias and Fiederer, Lukas and Glasstetter, Martin and Eggensperger, Katharina and Tangermann, Michael and Hutter, Frank and Burgard, Wolfram and Ball, Tonio (arXiv)(published)(bib)
    Deep learning with convolutional neural networks for EEG decoding and visualization
    In: Human Brain Mapping 38 (2017): 5391--5420

2016

  • Meinel, Andreas and Eggensperger, Katharina and Tangermann, Michael and Hutter, Frank (pdf)(bib)
    Hyperparameter Optimization for Machine Learning Problems in BCI (Abstract)
    In: Proceedings of the International Brain Computer Interface Meeting 2016
  • Schubert, Tobias and Eggensperger, Katharina and Gkogkidis, Alexis and Hutter, Frank and Ball, Tonio and Burgard, Wolfram (pdf)(bib)
    Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture
    In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA'16)
    Video showing the results of the optimization procedure

2015

  • Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina and Springenberg, Jost Tobias and Blum, Manuel and Hutter, Frank (preprint)(published)(supplementary)(poster)(bib)
    Efficient and Robust Automated Machine Learning
    In: Advances in Neural Information Processing Systems 28 (NeurIPS'15)
  • Feurer, Matthias and Klein, Aaron and Eggensperger, Katharina and Springenberg, Jost Tobias and Blum, Manuel and Hutter, Frank (pdf)(poster)(slides)(bib)
    Methods for Improving Bayesian Optimization for AutoML
    In: ICML 2015 AutoML Workshop
  • Katharina Eggensperger and Frank Hutter and Holger H. Hoos and Kevin Leyton-Brown (pdf)(poster)(bib)
    Efficient Benchmarking of Hyperparameter Optimizers via Surrogates
    In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence

2014

  • Eggensperger, Katharina and Hutter, Frank and Hoos, Holger H. and Leyton-Brown, Kevin (pdf)(slides)(bib)
    Surrogate Benchmarks for Hyperparameter Optimization
    In: ECAI workshop on Metalearning and Algorithm Selection (MetaSel)
    Superseeded by the AAAI15 paper Efficient Benchmarking of Hyperparameter Optimizers via Surrogates

2013

  • Eggensperger, Katharina and Feurer, Matthias and Hutter, Frank and Bergstra, James and Snoek, Jasper and Hoos, Holger H. and Leyton-Brown, Kevin (pdf)(poster)(bib)
    Towards an Empirical Foundation for Assessing Bayesian Optimization of Hyperparameters
    In: NeurIPS workshop on Bayesian Optimization in Theory and Practice
    Software and benchmarks are available from our HPOlib website.