9 citations · 41 across the 14 of their papers we have counts for
4 papers · 1 filter
Best Practices for Scientific Research on Neural Architecture Search
Marius Lindauer, Frank Hutter
Finding a well-performing architecture is often tedious for both DL practitioners and researchers, leading to tremendous interest in the automation of this task by means of neural…
Towards Assessing the Impact of Bayesian Optimization's Own Hyperparameters
Marius Lindauer, Matthias Feurer, Katharina Eggensperger +2
Bayesian Optimization (BO) is a common approach for hyperparameter optimization (HPO) in automated machine learning. Although it is well-accepted that HPO is crucial to obtain well…
BOAH: A Tool Suite for Multi-Fidelity Bayesian Optimization & Analysis of Hyperparameters
Marius Lindauer, Katharina Eggensperger, Matthias Feurer +4
Hyperparameter optimization and neural architecture search can become prohibitively expensive for regular black-box Bayesian optimization because the training and evaluation of a s…
Towards White-box Benchmarks for Algorithm Control
André Biedenkapp, H. Furkan Bozkurt, Frank Hutter +1
The performance of many algorithms in the fields of hard combinatorial problem solving, machine learning or AI in general depends on tuned hyperparameter configurations. Automated…