Automated Machine Learning - Methods, Systems, Challenges - researchr publication

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Frank Hutter, Lars Kotthoff, Joaquin Vanschoren, editors, Automated Machine Learning - Methods, Systems, Challenges. The Springer Series on Challenges in Machine Learning, Springer, 2019. [doi]

Abstract is missing.

Hyperparameter OptimizationMatthias Feurer, Frank Hutter. 3-33 [doi]

Meta-LearningJoaquin Vanschoren. 35-61 [doi]

Neural Architecture SearchThomas Elsken, Jan Hendrik Metzen, Frank Hutter. 63-77 [doi]

Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKALars Kotthoff, Chris Thornton, Holger H. Hoos, Frank Hutter, Kevin Leyton-Brown. 81-95 [doi]

Hyperopt-SklearnBrent Komer, James Bergstra, Chris Eliasmith. 97-111 [doi]

Auto-sklearn: Efficient and Robust Automated Machine LearningMatthias Feurer, Aaron Klein, Katharina Eggensperger, Jost Tobias Springenberg, Manuel Blum 0002, Frank Hutter. 113-134 [doi]

Towards Automatically-Tuned Deep Neural NetworksHector Mendoza, Aaron Klein, Matthias Feurer, Jost Tobias Springenberg, Matthias Urban, Michael Burkart, Maximilian Dippel, Marius Lindauer, Frank Hutter. 135-149 [doi]

TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine LearningRandal S. Olson, Jason H. Moore. 151-160 [doi]

The Automatic StatisticianChristian Steinruecken, Emma Smith, David Janz, James Robert Lloyd, Zoubin Ghahramani. 161-173 [doi]

Analysis of the AutoML Challenge Series 2015-2018Isabelle Guyon, Lisheng Sun-Hosoya, Marc Boullé, Hugo Jair Escalante, Sergio Escalera, Zhengying Liu, Damir Jajetic, Bisakha Ray, Mehreen Saeed, Michèle Sebag, Alexander R. Statnikov, Wei-Wei Tu, Evelyne Viegas. 177-219 [doi]

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