186
Bibliography
[97] Zehao Huang and Naiyan Wang. Data-driven sparse structure selection for deep neural
networks. In Proc. of ECCV, pages 304–320, 2018.
[98] Zhiqi Huang, Lu Hou, Lifeng Shang, Xin Jiang, Xiao Chen, and Qun Liu. Ghostbert:
Generate more features with cheap operations for bert. In Proceedings of the 59th
Annual Meeting of the Association for Computational Linguistics and the 11th Inter-
national Joint Conference on Natural Language Processing (Volume 1: Long Papers),
pages 6512–6523, 2021.
[99] Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Ben-
gio. Binarized neural networks. Advances in neural information processing systems,
29, 2016.
[100] Itay Hubara, Matthieu Courbariaux, Daniel Soudry, Ran El-Yaniv, and Yoshua Ben-
gio. Quantized neural networks: Training neural networks with low precision weights
and activations. The Journal of Machine Learning Research, 18(1):6869–6898, 2017.
[101] Itay Hubara, Yury Nahshan, Yair Hanani, Ron Banner, and Daniel Soudry. Improving
post training neural quantization: Layer-wise calibration and integer programming.
arXiv preprint arXiv:2006.10518, 2020.
[102] Sergey Ioffe and Christian Szegedy. Batch normalization: Accelerating deep network
training by reducing internal covariate shift. In Proceedings of International conference
on machine learning, pages 448–456, 2015.
[103] Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros. Image-to-image trans-
lation with conditional adversarial networks. In Proceedings of the IEEE Conference
on Computer Vision and Pattern Recognition, pages 1125–1134, 2017.
[104] Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew
Howard, Hartwig Adam, and Dmitry Kalenichenko.
Quantization and training of
neural networks for efficient integer-arithmetic-only inference. In Proceedings of the
IEEE conference on computer vision and pattern recognition, pages 2704–2713, 2018.
[105] Tianchu Ji, Shraddhan Jain, Michael Ferdman, Peter Milder, H Andrew Schwartz,
and Niranjan Balasubramanian.
On the distribution, sparsity, and inference-time
quantization of attention values in transformers. arXiv preprint arXiv:2106.01335,
2021.
[106] X. Jiao, Y. Yin, L. Shang, X. Jiang, X. Chen, L. Li, F. Wang, and Q. Liu. Tinybert:
Distilling bert for natural language understanding. In Findings of Empirical Methods
in Natural Language Processing, 2020.
[107] Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang,
and Qun Liu. Tinybert: Distilling bert for natural language understanding. arXiv
preprint arXiv:1909.10351, 2019.
[108] Amin Jourabloo and Xiaoming Liu. Pose-invariant 3d face alignment. In Proceedings
of the IEEE international conference on computer vision, pages 3694–3702, 2015.
[109] Felix Juefei-Xu, Vishnu Naresh Boddeti, and Marios Savvides. Local binary convo-
lutional neural networks. In Proceedings of the IEEE conference on computer vision
and pattern recognition, pages 19–28, 2017.