CSE 720: Compressed Sensing and Group Testing
This page refers to the Spring 2012 offering of CSE 720 only. The information on this page does not necessarily apply to every offering of CSE 720.
Spring 2012
15612
Compressed Sensing, Group Testing, and Applications
This is the second half of a year-long seminar on the general topic of sparse approximation, focusing on two central models of sparse approximation: combinatorial group testing, and compressive sensing. However, this second half can be taken independent of the first half . Compressive sensing is based on the idea that many signals can be represented with only a few non-zero coefficients (under a suitably chosen basis). These signals can be "measured" using relatively few linear measurements and can be reconstructed from the measurement vectors efficiently. This paradigm has found numerous applications in signal processing, data streaming, image processing, and so forth. In this part of the seminar we shall cover the basics of compressive sensing, from efficient measurement matrix constructions to efficient signal reconstruction. Lowerbounds with interesting connections to communications complexity are also covered.
Elementary probability theory
Ph.D.: This course does not fulfill core area or core course requirements.
M.S.: This course does not fulfill core area or core course requirements.
