Deep learning (DL) models have achieved impressive performance in various domains such
as medicine, finance, and autonomous vehicle systems with advances in computing power …

Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

The use and creation of machine‐learning‐based solutions to solve problems or reduce
their computational costs are becoming increasingly widespread in many domains. Deep …

Abstract Machine learning (ML) models are nowadays used in complex applications in
various domains, such as medicine, bioinformatics, and other sciences. Due to their black …

Zero-day malware samples pose a considerable danger to users as implicitly there are no
documented defences for previously unseen, newly encountered behaviour. Malware …

Interfaces for machine learning (ML), information and visualizations about models or data,
can help practitioners build robust and responsible ML systems. Despite their benefits …

The introduction of Transformer neural networks has changed the landscape of Natural
Language Processing during the last three years. While models inspired by it have …

This exploration aims to study the emotion recognition of speech and graphic visualization of
expressions of learners under the intelligent learning environment of the Internet. After …

Analysing data from experiments is a complex, multi‐step process, often with multiple
defensible choices available at each step. While analysts often report a single analysis …

Many statistical learning models hold an assumption that the training data and the future
unlabeled data are drawn from the same distribution. However, this assumption is difficult to …