The fields of both Natural Language Processing (NLP) and Automated Machine Learning
(AutoML) have achieved remarkable results over the past years. In NLP, especially Large …

Introduction The emergence of automated machine learning or AutoML has raised an
interesting trend of no-code and low-code machine learning where most tasks in the …

Wine grapes need frequent monitoring to achieve high yields and quality. Non-destructive
methods, such as proximal and remote sensing, are commonly used to estimate crop yield …

Automated machine learning (AutoML) strives for the automatic configuration of machine
learning algorithms and their composition into an overall (software) solution—a machine …

Common cross-validation (CV) methods like k-fold cross-validation or Monte Carlo cross-
validation estimate the predictive performance of a learner by repeatedly training it on a …

In this paper, we propose an innovative approach for robust prediction of processing tomato
yield using open-source AutoML techniques and statistical analysis. Sentinel-2 satellite …

Learning and predicting the performance of a configurable software system helps to provide
better quality assurance. One important engineering decision therein is how to encode the …

Carbon emissions trading has become an increasingly hot topic nowadays, due to the fact
that how to reduce carbon emissions has been a common effort of different countries …

Air pollution levels become more and more dangerous every year, which is one оf the most
significant and important problems for humanity nowadays. Of all air pollutants, particulate …

Optimizing a machine learning pipeline for a task at hand requires careful configuration of
various hyperparameters, typically supported by an AutoML system that optimizes the …