reference.md

Please cite if you use dedicated method.

Quantization related publications

1. LQnet:

@inproceedings{zhang2018lq,
  title={LQ-Nets: Learned Quantization for Highly Accurate and Compact Deep Neural Networks},
    author={Zhang, Dongqing and Yang, Jiaolong and Ye, Dongqiangzi and Hua, Gang},
      booktitle=ECCV,
        year={2018}
}

2. Dorefa-net

@article{zhou2016dorefa,
	title={DoReFa-Net: Training low bitwidth convolutional neural networks with low bitwidth gradients},
	author={Zhou, Shuchang and Wu, Yuxin and Ni, Zekun and Zhou, Xinyu and Wen, He and Zou, Yuheng},
	journal={arXiv preprint arXiv:1606.06160},
	year={2016}
}

3. PACT

@article{choi2018pact,
  title={Pact: Parameterized clipping activation for quantized neural networks},
  author={Choi, Jungwook and Wang, Zhuo and Venkataramani, Swagath and Chuang, Pierce I-Jen and Srinivasan, Vijayalakshmi and Gopalakrishnan, Kailash},
  journal={arXiv preprint arXiv:1805.06085},
  year={2018}
}

4. LSQ / TET

@inproceedings{esser2019learned,
  title={Learned step size quantization},
  author={Esser, Steven K and McKinstry, Jeffrey L and Bablani, Deepika and Appuswamy, Rathinakumar and Modha, Dharmendra S},
  booktitle=ICLR,
  year=2020
}

@misc{jin2019efficient,
    title={Towards Efficient Training for Neural Network Quantization},
    author={Qing Jin and Linjie Yang and Zhenyu Liao},
    year={2019},
    eprint={1912.10207},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

5. Xnor-Net / Xnor-Net++

% XNOR-net
@inproceedings{rastegari2016xnor,
	title={Xnor-net: Imagenet classification using binary convolutional neural networks},
	author={Rastegari, Mohammad and Ordonez, Vicente and Redmon, Joseph and Farhadi, Ali},
	booktitle=ECCV,
	pages={525--542},
	year={2016}
}

@misc{bulat2019xnornet,
    title={XNOR-Net++: Improved Binary Neural Networks},
    author={Adrian Bulat and Georgios Tzimiropoulos},
    year={2019},
    eprint={1909.13863},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

6. Bi-Real Net

@article{liu2018bi,
  title={Bi-Real Net: Binarizing Deep Network Towards Real-Network Performance},
  author={Liu, Zechun and Luo, Wenhan and Wu, Baoyuan and Yang, Xin and Liu, Wei and Cheng, Kwang-Ting},
  journal={arXiv preprint arXiv:1811.01335},
  year={2018}
}

7. Group-Net

@inproceedings{zhuang2019structured,
  title={Structured Binary Neural Network for Accurate Image Classification and Semantic Segmentation},
  author={Zhuang, Bohan and Shen, Chunhua and Tan, Mingkui and Liu, Lingqiao and Reid, Ian},
  booktitle=CVPR,
  year={2019}
}

8. TResnet (The work is not quantization oriented, but might insipre efficent inference)

@misc{ridnik2020tresnet,
    title={TResNet: High Performance GPU-Dedicated Architecture},
    author={Tal Ridnik and Hussam Lawen and Asaf Noy and Itamar Friedman and Emanuel Ben Baruch and Gilad Sharir},
    year={2020},
    eprint={2003.13630},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}

9. Fixup Initilization / Mixup (The work is not quantization oriented, but might insipre quantization in specific tasks)

@misc{zhang2019fixup,
    title={Fixup Initialization: Residual Learning Without Normalization},
    author={Hongyi Zhang and Yann N. Dauphin and Tengyu Ma},
    year={2019},
    eprint={1901.09321},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}

@misc{zhang2017mixup,
    title={mixup: Beyond Empirical Risk Minimization},
    author={Hongyi Zhang and Moustapha Cisse and Yann N. Dauphin and David Lopez-Paz},
    year={2017},
    eprint={1710.09412},
    archivePrefix={arXiv},
    primaryClass={cs.LG}
}