Statistics Colloquium: STA 290
Monday, January 13th at 4:10pm, MSB 1147 (Colloquium Room)
Join us for refreshments after the seminar in MSB 2208.
Speaker: Yaniv Plan, University of Michigan
Title: "Low-dimensionality in mathematical signal processing"
Abstract: Natural images tend to be compressible, i.e., the amount of information needed to encode an image is small. This conciseness of information -- in other words, low dimensionality of the signal -- is found throughout a plethora of applications ranging from MRI to quantum state tomography. It is natural to ask: can the number of measurements needed to determine a signal be comparable with the information content? We explore this question under modern models of low-dimensionality and measurement acquisition.