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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, M. and Klein, A. and Eggensperger, K. and Springenberg, J. and Blum, M. and Hutter, F. (preprint)(published)(supplementary)(poster)(bib)
    Efficient and Robust Automated Machine Learning
    In: Advances in Neural Information Processing Systems 28
  • 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, M. and Klein, A. and Eggensperger, K. and Springenberg, J. and Blum, M. and Hutter, F. (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

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