59 citations · 60 across the 6 of their papers we have counts for
7 papers
Scalable Class-Centric Visual Interactive Labeling
Matthias Matt, Jana Sedlakova, Jürgen Bernard +2
Large unlabeled datasets demand efficient and scalable data labeling solutions, in particular when the number of instances and classes is large. This leads to significant visual sc…
A Data-Centric Methodology and Task Typology for Time-Stamped Event Sequences
Yasara Peiris, Clara-Maria Barth, Elaine M. Huang +1
Task abstractions and taxonomic structures for tasks are useful for designers of interactive data analysis approaches, serving as design targets and evaluation criteria alike. For…
A Design Space for Explainable Ranking and Ranking Models
I. Al Hazwani, J. Schmid, M. Sachdeva +1
Item ranking systems support users in multi-criteria decision-making tasks. Users need to trust rankings and ranking algorithms to reflect user preferences nicely while avoiding sy…
Does the Layout Really Matter? A Study on Visual Model Accuracy Estimation
Nicolas Grossmann, Jürgen Bernard, Michael Sedlmair +1
In visual interactive labeling, users iteratively assign labels to data items until the machine model reaches an acceptable accuracy. A crucial step of this process is to inspect t…
ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion
Andreas Hinterreiter, Peter Ruch, Holger Stitz +4
Classifiers are among the most widely used supervised machine learning algorithms. Many classification models exist, and choosing the right one for a given task is difficult. Durin…
Speculative Execution for Guided Visual Analytics
Fabian Sperrle, Jürgen Bernard, Michael Sedlmair +2
We propose the concept of Speculative Execution for Visual Analytics and discuss its effectiveness for model exploration and optimization. Speculative Execution enables the automat…