Code and supplements for "Nostalgic Adam: Weighting more of the past gradients when designing the adaptive learning rate"
Haiwen Huang, Chang Wang, Bin Dong (http://bicmr.pku.edu.cn/~dongbin/Publications/NosAdam.pdf)
Dependencies: Python >= 3.5, Pytorch >= 0.4.0
An introduction to the paper in Chinese: https://zhuanlan.zhihu.com/p/65625686
If you find this code useful, please cite:
@inproceedings{ijcai2019-355,
title = {Nostalgic Adam: Weighting More of the Past Gradients When Designing the Adaptive Learning Rate},
author = {Huang, Haiwen and Wang, Chang and Dong, Bin},
booktitle = {Proceedings of the Twenty-Eighth International Joint Conference on
Artificial Intelligence, {IJCAI-19}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
pages = {2556--2562},
year = {2019},
month = {7},
doi = {10.24963/ijcai.2019/355},
url = {https://doi.org/10.24963/ijcai.2019/355},
}