Generalization in Deep Learning
With a direct analysis of neural networks, this paper presents a mathematically tight generalization theory to partially address an open problem regarding the generalization of deep learning. Unlike previous bound-based theory, our main theory is quantitatively as tight as possible for every dataset...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Published: |
2018
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1721.1/115274 |