Systems | Information | Learning | Optimization
 

High-dimensional low-rank matrix recovery

High-dimensional low-rank structure arises in many applications including genomics, signal processing, and social science. In this talk, we discuss some recent results on high-dimensional low-rank matrix recovery, including low-rank matrix recovery via rank-one projections and structured matrix completion. We provide theoretical justifications for the proposed methods and derive lower bounds …