The class is targeted to graduate and advanced undergraduate students. Space permitting, faculty and postdocs are also welcome.
Description: Tensors are multidimensional arrays, and many datasets are most naturally represented in this framework. This mini-course will introduce attendees to tensors decompositions, whose applications range from analysis of fluorescence data in chemistry, to brain imaging in neuroscience, to data compression of combustion simulations, to Internet traffic analysis in cybersecurity, and much more. The goals of this course are as follows:
Students will gain experience analyzing real data sets (in MATLAB).
Students should ideally have had a class in linear algebra or numerical analysis.
EVERY TUESDAY and THURSDAY, MAY 3 - MAY 17, 2022
10am - 11am
This is a combined CS and IEMS zero-credit course.