Deep Neural Networks in a Mathematical Framework
This SpringerBrief describes how to build a rigorous end-to-end mathematical framework for deep neural networks. The authors provide tools to represent and describe neural networks, casting previous results in the field in a more natural light. In particular, the authors derive gradient descent algo...
| Main Authors: | Caterini, Anthony L. (Author, http://id.loc.gov/vocabulary/relators/aut), Chang, Dong Eui (http://id.loc.gov/vocabulary/relators/aut) |
|---|---|
| Corporate Author: | SpringerLink (Online service) |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2018.
|
| Edition: | 1st ed. 2018. |
| Series: | SpringerBriefs in Computer Science,
|
| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
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