Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …

Interactive Machine Learning (IML) seeks to complement human perception and intelligence
by tightly integrating these strengths with the computational power and speed of computers …

We investigated the effects of example-based explanations for a machine learning classifier
on end users' appropriate trust. We explored the effects of spatial layout and visual …

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

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

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 …

Visual analytics systems combine machine learning or other analytic techniques with
interactive data visualization to promote sensemaking and analytical reasoning. It is through …

Dimensionality Reduction (DR) is a core building block in visualizing multidimensional data.
For DR techniques to be useful in exploratory data analysis, they need to be adapted to …

Supporting comparison is a common and diverse challenge in visualization. Such support is
difficult to design because solutions must address both the specifics of their scenario as well …

While the primary goal of visual analytics research is to improve the quality of insights and
findings, a substantial amount of research in provenance has focused on the history of …