Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review
The paper reviews and extends an emerging body of theoretical results on deep learning including the conditions under which it can be exponentially better than shallow learning. A class of deep convolutional networks represent an important special case of these conditions, though weight sharing is n...
Main Authors: | , , , , |
---|---|
Other Authors: | , , |
Format: | Article |
Language: | English |
Published: |
Institute of Automation, Chinese Academy of Sciences,
2017-03-23T19:40:31Z.
|
Subjects: | |
Online Access: | Get fulltext |