Learning curves provide insight into the dependence of a learner's generalization
performance on the training set size. This important tool can be used for model selection, to …

Earth observation (EO) is increasingly used for map** and monitoring processes
occurring at the surface of Earth. Data acquired by satellites nowadays allow us to have a …

Comparing different AutoML frameworks is notoriously challenging and often done
incorrectly. We introduce an open and extensible benchmark that follows best practices and …

Learning curves are a concept from social sciences that has been adopted in the context of
machine learning to assess the performance of a learning algorithm with respect to a certain …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

To reach high performance with deep learning, hyperparameter optimization (HPO) is
essential. This process is usually time-consuming due to costly evaluations of neural …

Liquid metals are highly conductive like metallic materials and have excellent deformability
due to their liquid state, making them rather promising for flexible and stretchable wearable …

State-of-the-art automated machine learning systems for tabular data often employ cross-
validation; ensuring that measured performances generalize to unseen data, or that …