|
View: |
Part 1: Document Description
|
|
Citation |
|
|---|---|
|
Title: |
The source codes of ADL Matlab |
|
Identification Number: |
doi:10.21979/N9/R97JSN |
|
Distributor: |
DR-NTU (Data) |
|
Date of Distribution: |
2020-04-14 |
|
Version: |
2 |
|
Bibliographic Citation: |
Ashfahani, A.; Pratama, Mahardhika, 2020, "The source codes of ADL Matlab", https://doi.org/10.21979/N9/R97JSN, DR-NTU (Data), V2 |
|
Citation |
|
|
Title: |
The source codes of ADL Matlab |
|
Identification Number: |
doi:10.21979/N9/R97JSN |
|
Authoring Entity: |
Ashfahani, A. |
|
Pratama, Mahardhika (Nanyang Technological University) |
|
|
Software used in Production: |
MATLAB |
|
Grant Number: |
NTU-SUTD AI Partnership Grant No. RGANS1902 |
|
Distributor: |
DR-NTU (Data) |
|
Access Authority: |
Pratama, Mahardhika |
|
Depositor: |
Pratama, Mahardhika |
|
Date of Deposit: |
2020-04-14 |
|
Holdings Information: |
https://doi.org/10.21979/N9/R97JSN |
|
Study Scope |
|
|
Keywords: |
Computer and Information Science, Computer and Information Science, codes and dataset |
|
Abstract: |
ADL codes and dataset |
|
Kind of Data: |
MATLAB codes and dataset |
|
Methodology and Processing |
|
|
Sources Statement |
|
|
Data Access |
|
|
Notes: |
Please refer to the LICENSE.md file in this dataset. |
|
Other Study Description Materials |
|
|
Related Publications |
|
|
Citation |
|
|
Identification Number: |
10.1137/1.9781611975673.75 |
|
Bibliographic Citation: |
Ashfahani, A., & Pratama, M. (2019, May). Autonomous deep learning: Continual learning approach for dynamic environments. In Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 666-674). Society for Industrial and Applied Mathematics. |
|
Label: |
ADL.m |
|
Notes: |
text/x-matlab |
|
Label: |
dataset |
|
Notes: |
text/plain; charset=US-ASCII |
|
Label: |
LICENSE.md |
|
Notes: |
text/markdown |
|
Label: |
README.md |
|
Notes: |
text/markdown |
|
Label: |
run_ADL.m |
|
Notes: |
text/x-matlab |