Learning matrix and functional models in high-dimensions
Statistical machine learning methods provide us with a principled framework for extracting meaningful information from noisy high-dimensional data sets. A significant feature of such procedures is that the inferences made are statistically significant, computationally efficient and scientifically me...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | en_US |
| Published: |
Georgia Institute of Technology
2014
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1853/52284 |