Unifying Low-Rank Models for Visual Learning
Many problems in signal processing, machine learning and computer vision can be solved by learning low rank models from data. In computer vision, problems such as rigid structure from motion have been formulated as an optimization over subspaces with fixed rank. These hard-rank constraints have trad...
| Main Author: | |
|---|---|
| Format: | Others |
| Published: |
Research Showcase @ CMU
2015
|
| Subjects: | |
| Online Access: | http://repository.cmu.edu/dissertations/506 http://repository.cmu.edu/cgi/viewcontent.cgi?article=1506&context=dissertations |