Frank Hutter

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Frank Hutter [1] Frank Hutter,

a German computer scientist, mathematician and professor at University of Freiburg. His research covers the fields of machine learning, automated machine learning, deep learning, neural architecture search, automated problem solving, stochastic optimization, stochastic gradient descent and Bayesian optimization. He defended his M.Sc. degree on stochastic local search at Darmstadt University of Technology in 2004 under Thomas Stützle and Holger H. Hoos, and his Ph.D. on Automating the Configuration of Algorithms for Solving Hard Computational Problems at University of British Columbia in 2009 under Holger H. Hoos, Kevin Leyton-Brown and Kevin P. Murphy.

Selected Publications

Frank Hutter, Dave A. D. Tompkins, Holger H. Hoos (2002). Scaling and Probabilistic Smoothing: Efficient Dynamic Local Search for SAT. CP 2002, pdf
Frank Hutter (2004). Stochastic Local Search for Solving the Most Probable Explanation Problem in Bayesian Networks. Diploma thesis (M.Sc.), Darmstadt University of Technology, supervisors Thomas Stützle and Holger H. Hoos, pdf

Ilya Loshchilov, Frank Hutter (2015). Online Batch Selection for Faster Training of Neural Networks. arXiv:1511.06343
Ilya Loshchilov, Frank Hutter (2016). CMA-ES for Hyperparameter Optimization of Deep Neural Networks. arXiv:1604.07269 [7]
Ilya Loshchilov, Frank Hutter (2016). SGDR: Stochastic Gradient Descent with Warm Restarts. arXiv:1608.03983
Thomas Elsken, Jan Hendrik Metzen, Frank Hutter (2017). Simple And Efficient Architecture Search for Convolutional Neural Networks. arXiv:1711.04528
Ilya Loshchilov, Frank Hutter (2017). Decoupled Weight Decay Regularization. arXiv:1711.05101
Jan van Rijn, Frank Hutter (2017). An Empirical Study of Hyperparameter Importance Across Datasets. AutoML@PKDD/ECML 2017, pdf
Patryk Chrabaszcz, Ilya Loshchilov, Frank Hutter (2018). Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari. arXiv:1802.08842 [8] [9]
Thomas Elsken, Jan Hendrik Metzen, Frank Hutter (2018). Neural Architecture Search: A Survey. arXiv:1808.05377
Marius Lindauer, Frank Hutter (2019). Best Practices for Scientific Research on Neural Architecture Search. arXiv:1909.02453
Lior Fuks, Noor Awad, Frank Hutter, Marius Lindauer (2019). An Evolution Strategy with Progressive Episode Lengths for Playing Games. IJCAI 2019, pdf
Frank Hutter, Lars Kotthoff, Joaquin Vanschoren (eds.) (2019). Automated Machine Learning. Springer