Joint Mathematics Colloquium 

University of Idaho

Washington State University


Spring 2013

Thursday,  March 28, 4:10-5:00 pm, room Neill Hall 5W

Refreshments in Neill 216 Hacker Reading Lounge at 3:30 pm

Geometric Methods in Image Processing, Networks, and Machine Learning

 

Andrea Bertozzi


Department of Mathematics

University of California Los Angeles


Abstract

Geometric methods have revolutionized the field of image processing and image analysis. I will review some of these classical methods including image snakes, total variation minimization, image segmentation methods
based on curve minimization, diffuse interface methods, and state of the art fast computational algorithms that include ideas from compressive sensing. Recently some of these concepts have shown promise for problems in
high dimensional data analysis and machine learning on graphs. I will give an overview of some of the classical results from imaging and ongoing work in high dimensional and network data.