Self-Distillation for Randomized Neural Networks
<p dir="ltr">Knowledge distillation (KD) is a conventional method in the field of deep learning that enables the transfer of dark knowledge from a teacher model to a student model, consequently improving the performance of the student model. In randomized neural networks, due to the...
Saved in:
| Main Author: | Minghui Hu (2457952) (author) |
|---|---|
| Other Authors: | Ruobin Gao (16003195) (author), Ponnuthurai Nagaratnam Suganthan (11274636) (author) |
| Published: |
2023
|
| Subjects: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ensemble Deep Random Vector Functional Link Neural Network for Regression
by: Minghui Hu (2457952)
Published: (2022) -
Automated layer-wise solution for ensemble deep randomized feed-forward neural network
by: Minghui Hu (2457952)
Published: (2022) -
Random vector functional link network: Recent developments, applications, and future directions
by: A.K. Malik (16003193)
Published: (2023) -
Stacked Ensemble Deep Random Vector Functional Link Network With Residual Learning for Medium-Scale Time-Series Forecasting
by: Ruobin Gao (16003195)
Published: (2025) -
Deep random vector functional link transformer network with multiple output layers for significant wave height forecasting
by: Aryan Bhambu (18767731)
Published: (2025)