3 citations · 3 across the 2 of their papers we have counts for
4 papers
BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization
Carl Hvarfner, Danny Stoll, Artur Souza +3
Bayesian optimization (BO) has become an established framework and popular tool for hyperparameter optimization (HPO) of machine learning (ML) algorithms. While known for its sampl…
Winning solutions and post-challenge analyses of the ChaLearn AutoDL challenge 2019
Zhengying Liu, Adrien Pavao, Zhen Xu +22
This paper reports the results and post-challenge analyses of ChaLearn's AutoDL challenge series, which helped sorting out a profusion of AutoML solutions for Deep Learning (DL) th…
Hyperparameter Transfer Across Developer Adjustments
Danny Stoll, Jörg K. H. Franke, Diane Wagner +2
After developer adjustments to a machine learning (ML) algorithm, how can the results of an old hyperparameter optimization (HPO) automatically be used to speedup a new HPO? This q…
Learning to Design RNA
Frederic Runge, Danny Stoll, Stefan Falkner +1
Designing RNA molecules has garnered recent interest in medicine, synthetic biology, biotechnology and bioinformatics since many functional RNA molecules were shown to be involved…