Rapid Sampling for Visualizations with Ordering Guarantees.

Visualizations are frequently used as a means to understand trends and gather insights from datasets, but often take a long time to generate. In this paper, we focus on the problem of . Our primary focus will be on sampling algorithms that preserve the visual property of ; our techniques will also apply to some other visual properties.

Motif Discovery in Physiological Datasets: A Methodology for Inferring Predictive Elements.

In this article, we propose a methodology for identifying predictive physiological patterns in the absence of prior knowledge. We use the principle of conservation to identify activity that consistently precedes an outcome in patients, and describe a two-stage process that allows us to efficiently search for such patterns in large datasets. This involves first transforming continuous physiological signals from patients into symbolic sequences, and then searching for patterns in these reduced representations that are strongly associated with an outcome.