This is a PyTorch implementation of the Variational-HyperAdam algorithm from our TPAMI paper:
Title: Variational-HyperAdam: A Meta-learning Appproach to Network Training
Authors: Shipeng Wang, Yan Yang, Jian Sun, Zongben Xu
Email: wangshipeng8128@stu.xjtu.edu.cn; wangshipeng8128@gmail.com
Institution: School of Mathematics and Statistics, Xi'an Jiaotong University
Link: https://ieeexplore.ieee.org/document/9361276
To replicate the experiments,run from terminal:
cd HyperAdam
sh batch_process.sh
Requirement: PyTorch >= 1.0, Python 3.7
If the code is useful in your research, please cite ourpaper:
@ARTICLE{vrhyperadam2021wang,
author={S. {Wang} and Y. {Yang} and J. {Sun} and Z. {Xu}},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={Variational HyperAdam: A Meta-learning Approach to Network Training},
year={2021},
volume={},
number={},
pages={1-1},
doi={10.1109/TPAMI.2021.3061581}
}