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    Author information
    First name: Frank
    Last name: Hutter
    DBLP: 89/5383
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    Below you find the publications which have been written by this author.

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    Journal article
    Katharina Eggensperger, Marius Thomas Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown.
    Efficient benchmarking of algorithm configurators via model-based surrogates.
    Machine Learning 2018, Volume 107 (0) 2018
    Journal article
    Frank Hutter, Marius Thomas Lindauer, Adrian Balint, Sam Bayless, Holger H. Hoos, Kevin Leyton-Brown.
    The Configurable SAT Solver Challenge (CSSC).
    Artif. Intell. 2017, Volume 243 (0) 2017
    Conference paper
    Andre Biedenkapp, Marius Thomas Lindauer, Katharina Eggensperger, Frank Hutter, Chris Fawcett, Holger H. Hoos.
    Efficient Parameter Importance Analysis via Ablation with Surrogates.
    Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, February 4-9, 2017, San Francisco, California, USA. 2017 (0) 2017
    Conference paper
    Katharina Eggensperger, Marius Thomas Lindauer, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown.
    Efficient Benchmarking of Algorithm Configuration Procedures via Model-Based Surrogates.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Robin Tibor Schirrmeister, Jost Tobias Springenberg, Lukas Dominique Josef Fiederer, Martin Glasstetter, Katharina Eggensperger, Michael Tangermann, Frank Hutter, Wolfram Burgard, Tonio Ball.
    Deep learning with convolutional neural networks for brain mapping and decoding of movement-related information from the human EEG.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Katharina Eggensperger, Marius Thomas Lindauer, Frank Hutter.
    Pitfalls and Best Practices in Algorithm Configuration.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter.
    Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets.
    Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, AISTATS 2017, 20-22 April 2017, Fort Lauderdale, FL, USA 2017 (0) 2017
    Conference paper
    Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter.
    A Downsampled Variant of ImageNet as an Alternative to the CIFAR datasets.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Marius Thomas Lindauer, Frank Hutter, Holger H. Hoos, Torsten Schaub.
    AutoFolio: An Automatically Configured Algorithm Selector (Extended Abstract).
    Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017 2017 (0) 2017
    Journal article
    Lars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown.
    Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA.
    Journal of Machine Learning Research 2017, Volume 18 (0) 2017
    Conference paper
    Bernd Bischl, Giuseppe Casalicchio, Matthias Feurer, Frank Hutter, Michel Lang, Rafael Gomes Mantovani, Jan N. van Rijn, Joaquin Vanschoren.
    OpenML Benchmarking Suites and the OpenML100.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Robin Tibor Schirrmeister, Lukas Gemein, Katharina Eggensperger, Frank Hutter, Tonio Ball.
    Deep learning with convolutional neural networks for decoding and visualization of EEG pathology.
    CoRR 2017, Volume 0 (0) 2017
    Journal article
    Marius Thomas Lindauer, Frank Hutter.
    Warmstarting of Model-based Algorithm Configuration.
    CoRR 2017, Volume 0 (0) 2017
    Journal article
    Katharina Eggensperger, Marius Thomas Lindauer, Frank Hutter.
    Predicting Runtime Distributions using Deep Neural Networks.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Jan N. van Rijn, Frank Hutter.
    Hyperparameter Importance Across Datasets.
    CoRR 2017, Volume 0 (0) 2017
    Journal article
    Ilya Loshchilov, Frank Hutter.
    Fixing Weight Decay Regularization in Adam.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Thomas Elsken, Jan Hendrik Metzen, Frank Hutter.
    Simple And Efficient Architecture Search for Convolutional Neural Networks.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    James T. Wilson, Riccardo Moriconi, Frank Hutter, Marc Peter Deisenroth.
    The reparameterization trick for acquisition functions.
    CoRR 2017, Volume 0 (0) 2017
    Conference paper
    Jan N. van Rijn, Frank Hutter.
    An Empirical Study of Hyperparameter Importance Across Datasets.
    Proceedings of the International Workshop on Automatic Selection, Configuration and Composition of Machine Learning Algorithms co-located with the European Conference on Machine Learning Principles and Practice of Knowledge Discovery in Databases, AutoML 2017 (0) 2017
    Conference paper
    Ziyu Wang 0001, Frank Hutter, Masrour Zoghi, David Matheson, Nando de Freitas.
    Bayesian Optimization in a Billion Dimensions via Random Embeddings.
    J. Artif. Intell. Res. (JAIR) 2016, Volume 55 (0) 2016
    Conference paper
    Ilya Loshchilov, Frank Hutter.
    CMA-ES for Hyperparameter Optimization of Deep Neural Networks.
    CoRR 2016, Volume 0 (0) 2016
    Conference paper
    Aaron Klein, Stefan Falkner, Simon Bartels, Philipp Hennig, Frank Hutter.
    Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets.
    CoRR 2016, Volume 0 (0) 2016
    Journal article
    Bernd Bischl, Pascal Kerschke, Lars Kotthoff, Marius Thomas Lindauer, Yuri Malitsky, Alexandre Fréchette, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown, Kevin Tierney, Joaquin Vanschoren.
    ASlib: A benchmark library for algorithm selection.
    Artif. Intell. 2016, Volume 237 (0) 2016
    Conference paper
    Tobias Schubert 0002, Katharina Eggensperger, Alexis Gkogkidis, Frank Hutter, Tonio Ball, Wolfram Burgard.
    Automatic bone parameter estimation for skeleton tracking in optical motion capture.
    2016 IEEE International Conference on Robotics and Automation, ICRA 2016, Stockholm, Sweden, May 16-21, 2016 2016 (0) 2016
    Conference paper
    Ilya Loshchilov, Frank Hutter.
    SGDR: Stochastic Gradient Descent with Restarts.
    CoRR 2016, Volume 0 (0) 2016
    Show item 1 to 25 of 84  

    Your query returned 84 matches in the database.