Auxiliary network design for local learning in deep neural networks
The training of deep neural networks utilizes the backpropagation algorithm which consists of the forward pass, backward pass and parameters update. The output of a certain layer is produced based on the output of its lower layers in a sequential manner, and the gradients can only flow back layer by...
Main Author: | Peng, Jiawei |
---|---|
Other Authors: | Lin Zhiping |
Format: | Final Year Project (FYP) |
Language: | English |
Published: |
Nanyang Technological University
2021
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/149869 |
Similar Items
-
Deep learning neural network for image processing
by: Ma, Xueqing
Published: (2020) -
Learn to navigate through deep neural networks
by: Wu, Keyu
Published: (2020) -
Deep learning neural networks for NAO robot control
by: Tee, Enid Mun Xin
Published: (2019) -
Online and continual learning using randomization based deep neural networks
by: Sreenivasan, Shiva
Published: (2023) -
Stock trading & prediction using deep learning neural networks
by: Gowri, Kannan
Published: (2017)