A Projected Subgradient Method for Scalable Multi-Task Learning
Recent approaches to multi-task learning have investigated the use of a variety of matrix norm regularization schemes for promoting feature sharing across tasks.In essence, these approaches aim at extending the l1 framework for sparse single task approximation to the multi-task setting. In this pape...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Published: |
2008
|
| Online Access: | http://hdl.handle.net/1721.1/41888 |