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 …

In the age of big data, all forms of data with increasing samples and high-dimensional
characteristics are demonstrating their importance in a variety of fields, including data …

Inspired by the great success of machine learning (ML), researchers have applied ML
techniques to visualizations to achieve a better design, development, and evaluation of …

A time-frequency diagram is a commonly used visualization for observing the time-frequency
distribution of radio signals and analyzing their time-varying patterns of communication …

Visualization and artificial intelligence (AI) are well-applied approaches to data analysis. On
one hand, visualization can facilitate humans in data understanding through intuitive visual …

Programming instructors often conduct in-class exercises to help them identify students that
are falling behind and surface students' misconceptions. However, as we found in interviews …

Dimensionality reduction (DR) is frequently used for analyzing and visualizing high-
dimensional data as it provides a good first glance of the data. However, to interpret the DR …

Dimensionality reduction has many applications in data visualization and machine learning.
Existing methods can be classified into global ones and local ones. The global methods …

Data-driven problem solving in many real-world applications involves analysis of time-
dependent multivariate data, for which dimensionality reduction (DR) methods are often …

During exploratory visual analysis (EVA), analysts need to continually determine which
subsequent activities to perform, such as which data variables to explore or how to present …