ECE 598 ZZ

Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

High Dimensional Geometric Data Analysis This course aims to establish the mathematical foundation of many recent algorithms for tasks such as organization and visualization of data clouds, dimensionality reduction, clustering, classification, and regression. "Data analysis" is an interdisciplinary field. It combines mathematics (both poor and applied), computer science (machine learning, theoretical CS, AI, computer vision), electrical engineering (signal and image processing) statistics, structural biology, neuroscience (fMRI), computation biology (microarray data for gene expression), finance (financial data), biophysics and chemical engineering (molecular dynamics simulations), World Wide Web and search (link analysis), social networks, psychology (MMPI questioners), and more. We will focus on a few particular methods and explain where they are most appropriately applied, what are their limitations, and what is the underlying math, so we will develop a good sense of when to apply t