Multitask Deep Learning models for real-time deployment in embedded systems
Multitask Learning (MTL) was conceived as an approach to improve thegeneralization ability of machine learning models. When applied to neu-ral networks, multitask models take advantage of sharing resources forreducing the total inference time, memory footprint and model size. Wepropose MTL as a way...
| Main Author: | |
|---|---|
| Format: | Others |
| Language: | English |
| Published: |
KTH, Robotik, perception och lärande, RPL
2017
|
| Subjects: | |
| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-216673 |