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

Abstract Information visualization (InfoVis), the study of transforming data, information, and
knowledge into interactive visual representations, is very important to users because it …

Dimensionality reduction methods, also known as projections, are frequently used in
multidimensional data exploration in machine learning, data science, and information …

Massive simulations and arrays of sensing devices, in combination with increasing
computing resources, have generated large, complex, high-dimensional datasets used to …

In machine learning, pattern classification assigns high-dimensional vectors (observations)
to classes based on generalization from examples. Artificial neural networks currently …

Visual analysis of multidimensional data requires expressive and effective ways to reduce
data dimensionality to encode them visually. Multidimensional projections (MDP) figure …

Progressive Visual Analytics aims at improving the interactivity in existing analytics
techniques by means of visualization as well as interaction with intermediate results. One …

t-Distributed Stochastic Neighbor Embedding (t-SNE) for the visualization of
multidimensional data has proven to be a popular approach, with successful applications in …

Designing a complete visualization system involves many subtle decisions. When designing
a complex, real-world visualization system, such decisions involve many types of …

Visual analytics employs interactive visualizations to integrate users' knowledge and
inference capability into numerical/algorithmic data analysis processes. It is an active …