198

Bibliography

[263] Sheng Xu, Zhendong Liu, Xuan Gong, Chunlei Liu, Mingyuan Mao, and Baochang

Zhang. Amplitude suppression and direction activation in networks for 1-bit faster

r-cnn. In Proceedings of the 4th International Workshop on Embedded and Mobile

Deep Learning, pages 19–24, 2020.

[264] Sheng Xu, Junhe Zhao, Jinhu Lu, Baochang Zhang, Shumin Han, and David Doer-

mann. Layer-wise searching for 1-bit detectors. In Proceedings of the IEEE/CVF

Conference on Computer Vision and Pattern Recognition, pages 5682–5691, 2021.

[265] Yuhui Xu, Lingxi Xie, Xiaopeng Zhang, Xin Chen, Guo-Jun Qi, Qi Tian, and Hongkai

Xiong. Pc-darts: Partial channel connections for memory-efficient architecture search.

arXiv preprint arXiv:1907.05737, 2019.

[266] Zhe Xu and Ray CC Cheung. Accurate and compact convolutional neural networks

with trained binarization. arXiv preprint arXiv:1909.11366, 2019.

[267] Zihan Xu, Mingbao Lin, Jianzhuang Liu, Jie Chen, Ling Shao, Yue Gao, Yonghong

Tian, and Rongrong Ji. Recu: Reviving the dead weights in binary neural networks.

arXiv preprint arXiv:2103.12369, 2021.

[268] Haojin Yang, Martin Fritzsche, Christian Bartz, and Christoph Meinel. Bmxnet: An

open-source binary neural network implementation based on mxnet. In Proceedings

of the 25th ACM international conference on Multimedia, pages 1209–1212, 2017.

[269] Li Yang, Zhezhi He, and Deliang Fan. Binarized depthwise separable neural network

for object tracking in fpga. In Proceedings of the 2019 on Great Lakes Symposium on

VLSI, pages 347–350, 2019.

[270] Zhewei Yao, Amir Gholami, Qi Lei, Kurt Keutzer, and Michael W Mahoney. Hessian-

based analysis of large batch training and robustness to adversaries.

Advances in

Neural Information Processing Systems, 31, 2018.

[271] Dong Yi, Zhen Lei, Shengcai Liao, and Stan Z Li. Deep metric learning for person re-

identification. In Proceedings of the International Conference on Pattern Recognition,

pages 34–39, 2014.

[272] Penghang Yin, Shuai Zhang, Jiancheng Lyu, Stanley Osher, Yingyong Qi, and Jack

Xin. Binaryrelax: A relaxation approach for training deep neural networks with quan-

tized weights. SIAM Journal on Imaging Sciences, 11(4):2205–2223, 2018.

[273] Shouyi Yin, Peng Ouyang, Shixuan Zheng, Dandan Song, Xiudong Li, Leibo Liu, and

Shaojun Wei. A 141 uw, 2.46 pj/neuron binarized convolutional neural network based

self-learning speech recognition processor in 28nm cmos. In 2018 IEEE Symposium

on VLSI Circuits, pages 139–140. IEEE, 2018.

[274] C. Ying, A. Klein, E. Real, E. Christiansen, K. Murphy, and F. Hutter. Nas-bench-

101: Towards reproducible neural architecture search. In ICML, 2019.

[275] Yang You, Jing Li, Sashank Reddi, Jonathan Hseu, Sanjiv Kumar, Srinadh Bhojana-

palli, Xiaodan Song, James Demmel, Kurt Keutzer, and Cho-Jui Hsieh. Large batch

optimization for deep learning: Training bert in 76 minutes. Proc. of ICLR, pages

1–37, 2020.

[276] Jiahui Yu, Yuning Jiang, Zhangyang Wang, Zhimin Cao, and Thomas Huang. Unit-

box: An advanced object detection network. In Proceedings of the 24th ACM inter-

national conference on Multimedia, pages 516–520, 2016.