*********************************
There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
*********************************
Title: Learning to Adapt under Practical Sensing Constraints
Committee:
Dr. Davenport, Advisor
Dr. Rozell, Chair
Dr. Romberg
Abstract:
The objective of the proposed research is to combine theory in signal processing and machine learning to develop techniques for adaptive signal acquisition which can cope with practical measurement constraints. By leveraging structured data models such as sparsity, intelligent sampling schemes can enable higher quality estimation with less labeled data in diverse applications such as imaging, recommendation systems, information retrieval, and psychometric studies. The proposed work will target three aims: (i) investigate the best selection of observations for linear regression, (ii) develop theory for localizing a point via sequentially-chosen paired comparisons, and (iii) design methods for adaptive measurement selection in one-bit constrained sensing.
