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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

  • Feurer, Matthias and van Rijn, Jan N. and Kadra, Arlind and Gijsbers, Pieter and Mallik, Neeratyoy and Ravi, Sahithya and Müller, Andreas and Vanschoren, Joaquin and Hutter, Frank (arXiv)(bib)
    OpenML-Python: an extensible Python API for OpenML
    In: arXiv 1911.02490 (2019): 1-5
  • Bischl, Bernd and Casalicchio, Giuseppe and Feurer, Matthias and Hutter, Frank and Lang, Michel and Mantovani, Rafael G. and van Rijn, Jan N. and Vanschoren, Joaquin (arXiv)(bib)
    OpenML Benchmarking Suites
    In: arXiv 1708.0373v2 (2019): 1-6
  • 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 Hutter, Frank (arXiv)(published)(bib)
    Hyperparameter Optimization
    In: AutoML: Methods, Sytems, Challenges
  • Mendoza, Hector and Klein, Aaron and Feurer, Matthias and Springenberg, Jost Tobias and Urban, Matthias and Burkart, Michael and Dippel, Max and Lindauer, Marius and Hutter, Frank (arXiv)(published)(bib)
    Towards Automatically-Tuned Deep Neural Networks
    In: AutoML: Methods, Sytems, Challenges
  • 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

2018

  • Feurer, Matthias and Letham, Benjamin and Bakshy, Eytan (arXiv)(pdf)(bib)
    Scalable Meta-Learning for Bayesian Optimization using Ranking-Weighted Gaussian Process Ensembles
    In: ICML 2018 AutoML Workshop
  • 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
  • Feurer, M. and Hutter, F. (pdf)(bib)
    Towards Further Automation in AutoML
    In: ICML 2018 AutoML Workshop

2017

  • Bischl, Bernd and Casalicchio, Giuseppe and Feurer, Matthias and Hutter, Frank and Lang, Michel and Mantovani, Rafael G. and van Rijn, Jan N. and Vanschoren, Joaquin (arXiv)(bib)
    OpenML Benchmarking Suites and the OpenML100
    In: arXiv 1708.0373v1 (2017): 1-6

2016

  • Mendoza, H. and Klein, A. and Feurer, M. and Springenberg, J. and Hutter, F. (pdf)(poster)(bib)
    Towards Automatically-Tuned Neural Networks
    In: ICML 2016 AutoML Workshop

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)
  • Vanschoren, J. and van Rijn, J. and Bischl, B. and Casalicchio, G. and Lang, M. and Feurer, M. (pdf)(bib)
    OpenML: a Networked Science Platform for Machine Learning (Abstract)
    In: ICML 2015 MLOSS Workshop
  • 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
  • Matthias Feurer and Tobias Springenberg and Frank Hutter (pdf)(supplementary)(poster)(bib)
    Initializing Bayesian Hyperparameter Optimization via Meta-Learning
    In: Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence

2014

  • Matthias Feurer and Tobias Springenberg and Frank Hutter (pdf)(slides)(bib)
    Using Meta-Learning to Initialize Bayesian Optimization of Hyperparameters
    In: ECAI workshop on Metalearning and Algorithm Selection (MetaSel)
    Superseeded by the AAAI15 paper Initializing Bayesian Hyperparameter Optimization via Meta-Learning

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.