Deep virtual networks for memory efficient inference of multiple tasks
Deep networks consume a large amount of memory by their nature. A natural question arises can we reduce that memory requirement whilst maintaining performance. In particular, in this work we address the problem of memory efficient learning for multiple tasks. To this end, we propose a novel network...
| Main Authors: | , , , |
|---|---|
| Format: | Conference item |
| Published: |
IEEE
2020
|