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Lukas Tuggener, Mohammadreza Amirian, Fernando Benites, Pius von Däniken, Prakhar Gupta, Frank-Peter Schilling and Thilo Stadelmann
We present an extensive evaluation of a wide variety of promising design patterns for automated deep-learning (AutoDL) methods, organized according to the problem categories of the 2019 AutoDL challenges, which set the task of optimizing both model accur...
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