Lecturer: Dustin Mixon
Fields: Mathematical Data Science
Given several points in a high-dimensional space, we would like to cluster the points according to similarity. But how can one find the best clustering? In this talk, we show how eigenvectors point to the solution.
Dustin Mixon received his PhD in applied and computational mathematics from Princeton University in 2012. He specializes in applied harmonic analysis and mathematical data science.
Affiliation: The Ohio State University