104 citations · 128 across the 8 of their papers we have counts for
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cs.LG2022★ 104 cited
Multi-Objective Hyperparameter Optimization in Machine Learning -- An Overview
Florian Karl, Tobias Pielok, Julia Moosbauer +10
Hyperparameter optimization constitutes a large part of typical modern machine learning workflows. This arises from the fact that machine learning methods and corresponding preproc…
cs.LG2022★ 4 cited
Improving Accuracy of Interpretability Measures in Hyperparameter Optimization via Bayesian Algorithm Execution
Julia Moosbauer, Giuseppe Casalicchio, Marius Lindauer +1
Despite all the benefits of automated hyperparameter optimization (HPO), most modern HPO algorithms are black-boxes themselves. This makes it difficult to understand the decision p…