ECE PhD Defense: "Clustering with Flexible Constraints and Application to Disease Subtyping," Yale Chang
Abstract: Clustering algorithms are widely used to extract knowledge from large amount of unlabeled data (such as, discovering subtypes of complex diseases to enable personalized treatments of patients). Clustering is a challenging problem because given the same data, samples can be grouped in multiple different perspectives (views). Which of these alternative groupings is useful depends on the application. Thus, incorporating domain expert input often improves clustering performance. In this dissertation, we explore various ways to incorporate expert input to guide clustering. First, domain...
Wednesday, November 29, 2017 at 10:00am
No recent activity