- Series
- Job Candidate Talk
- Time
- Thursday, January 16, 2014 - 11:05am for 1 hour (actually 50 minutes)
- Location
- Skiles 006
- Speaker
- Yaniv Plan – University of Michigan – http://www.yanivplan.com/
- Organizer
- Yuri Bakhtin
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.