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 …

Interactive machine learning (IML) is an iterative learning process that tightly couples a
human with a machine learner, which is widely used by researchers and practitioners to …

In this work, we present a study that traces the technical and cognitive processes in two
visual analytics applications to a common theoretic model of soft knowledge that may be …

In the age of big data, being able to make sense of data is an important key to success.
Interactive Visual Data Analysis advocates the synthesis of visualization, interaction, and …

Computational models, such as simulations, are central to a wide range of fields in science
and industry. Those models take input parameters and produce some output. To fully exploit …

Interactive machine learning (IML) is a learning process in which a user interacts with a
system to iteratively define and optimise a model. Although recent years have illustrated the …

This work presents an approach to support the visual analysis of parameter dependencies of
time‐series segmentation. The goal is to help analysts understand which parameters have …

With the development of science and technology, it is possible to analyze residents' daily
behaviors for the purpose of smart healthcare in the smart home environment. Many …

For the automatic segmentation of multivariate time series domain experts at first need to
consider a huge space of alternative configurations of algorithms and parameters. We …

Segmenting biologging time series of animals on multiple temporal scales is an essential
step that requires complex techniques with careful parameterization and possibly cross …