Random vector functional link network based shallow and deep learning
Deep learning has been extremely successful in recent years. However, it should be noted that neural networks utilizing back-propagation for parameter training are subject to a time-intensive drawback. Also, these neural networks may fall into local minima and give sub-optimal results. At the same t...
Saved in:
Main Author: | Shi, Qiushi |
---|---|
Other Authors: | Ponnuthurai Nagaratnam Suganthan |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2023
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/171612 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Ensemble deep random vector functional link neural net for imbalanced datasets
by: Soo, Jian Xian
Published: (2022) -
Random vector functional link neural network based ensemble deep learning
by: Shi, Qiushi, et al.
Published: (2022) -
Weighting and pruning based ensemble deep random vector functional link network for tabular data classification
by: Shi, Qiushi, et al.
Published: (2023) -
Jointly optimized ensemble deep random vector functional link network for semi-supervised classification
by: Shi, Qiushi, et al.
Published: (2022) -
Random vector functional link neural network based deep learning for regression
by: Chion, Jet Herng
Published: (2020)