ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks

Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Lin

Accepted by ICML 2022. More Info: [ Paper | Slide | Youtube | Github ]

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Usages

See CV and NLP folders for the detailed implementation.

• NLP models are inspired and developed based on fairseq and HAT.
• CV models are inspired and developed based on BossNAS and Autoformer.

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Citation

If you find this codebase is useful for your research, please cite:

@inproceedings{ShiftAddNet,
title={ShiftAddNet: A Hardware-Inspired Deep Network},
author={Haoran You, Xiaohan Chen, Yongan Zhang, Chaojian Li, Sicheng Li, Zihao Liu, Zhangyang Wang, Yingyan Lin},
booktitle={Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS)},
year={2020},
}

@inproceedings{ShiftAddNAS,
title={ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks},
author={Haoran You, Baopu Li, Huihong Shi, Yonggan Fu, Yingyan Lin},
booktitle={Thirty-ninth International Conference on Machine Learning (ICML)},
year={2022},
}