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Cieran: Designing Sequential Colormaps via In-Situ Active Preference Learning
In an evaluation with twelve scientists, we found that Cieran effectively modeled user preferences to rank colormaps and leveraged this model to create new quality designs.
CLAMS: A Cluster Ambiguity Measure for Estimating Perceptual Variability in Visual Clustering
In this research, we study perceptual variability in conducting visual clustering, which we call Cluster Ambiguity.
Scholastic: Graphical Human-Al Collaboration for Inductive and Interpretive Text Analysis
Scholastic demonstrates how human-centered algorithm design and visualizations employing familiar metaphors can support inductive and interpretive research methodologies through interactive topic modeling and document clustering.
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