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Normalization has become one of the most fundamental components in many deep neural networks for machine learning tasks while deep neural network has also been widely used in CTR estimation field.
Ad Click Prediction: A View from the Trenches. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD ’13) . Association for Computing Machinery, New York, NY, USA, 1222–1230
H. Brendan McMahan, Gary Holt, D. Sculley, Michael Young, Dietmar Ebner, Julian Grady, Lan Nie, Todd Phillips, Eugene Davydov, Daniel Golovin, and et al. 2013 · 2013
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Practical lessons from predicting clicks on ads at facebook. In Proceedings of the Eighth International Workshop on Data Mining for Online Advertising . ACM, 1–9
Xinran He, Junfeng Pan, Ou Jin, Tianbing Xu, Bo Liu, Tao Xu, Yanxin Shi, Antoine Atallah, Ralf Herbrich, Stuart Bowers, et al · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy. 2015 · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016 · 2016
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Wide & deep learning for recommender systems. In Proceedings of the 1st workshop on deep learning for recommender systems . ACM, 7–10
Heng-Tze Cheng, Levent Koc, Jeremiah Harmsen, Tal Shaked, Tushar Chandra, Hrishi Aradhye, Glen Anderson, Greg Corrado, Wei Chai, Mustafa Ispir, et al · 2016
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Product-based neural networks for user response prediction. In 2016 IEEE 16th International Conference on Data Mining (ICDM) . IEEE, 1149–1154
Yanru Qu, Han Cai, Kan Ren, Weinan Zhang, Yong Yu, Ying Wen, and Jun Wang. 2016 · 2016
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Deep learning over multi-field categorical data. In European conference on information retrieval . Springer, 45–57
Weinan Zhang, Tianming Du, and Jun Wang. 2016 · 2016
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DeepFM: a factorization-machine based neural network for CTR prediction
Huifeng Guo, Ruiming Tang, Yunming Ye, Zhenguo Li, and Xiuqiang He. 2017 · 2017
Cited alongside, same era.
Neural factorization machines for sparse predictive analytics. In Proceedings of the 40th International ACM SIGIR conference on Research and Development in Information Retrieval . 355–364
Xiangnan He and Tat-Seng Chua. 2017 · 2017
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Deep & cross network for ad click predictions. In Proceedings of the ADKDD’17 . ACM, 12
Ruoxi Wang, Bin Fu, Gang Fu, and Mingliang Wang. 2017 · 2017
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Jun Xiao, Hao Ye, Xiangnan He, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. 2017 · 2017
Cited alongside, same era.
Group normalization. In Proceedings of the European Conference on Computer Vision (ECCV) . 3–19
Yuxin Wu and Kaiming He. 2018 · 2018
Later among the works it cites.
Guorui Zhou, Xiaoqiang Zhu, Chenru Song, Ying Fan, Han Zhu, Xiao Ma, Yanghui Yan, Junqi Jin, Han Li, and Kun Gai. 2018 · 2018
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FiBiNET: combining feature importance and bilinear feature interaction for click-through rate prediction. In Proceedings of the 13th ACM Conference on Recommender Systems . 169–177
Tongwen Huang, Zhiqi Zhang, and Junlin Zhang. 2019 · 2019
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Autoint: Automatic feature interaction learning via self-attentive neural networks. In Proceedings of the 28th ACM International Conference on Information and Knowledge Management . 1161–1170
Weiping Song, Chence Shi, Zhiping Xiao, Zhijian Duan, Yewen Xu, Ming Zhang, and Jian Tang. 2019 · 2019
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Alex Beutel, Paul Covington, Sagar Jain, Can Xu, Jia Li, Vince Gatto, and Ed H Chi. 2018 · 2018
Cited alongside, same era.
xdeepfm: Combining explicit and implicit feature interactions for recommender systems. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . ACM, 1754–1763
Jianxun Lian, Xiaohuan Zhou, Fuzheng Zhang, Zhongxia Chen, Xing Xie, and Guangzhong Sun. 2018 · 2018
Cited alongside, same era.
How does batch normalization help optimization?. In Advances in Neural Information Processing Systems . 2483–2493
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, and Aleksander Madry. 2018 · 2018
Cited alongside, same era.
Understanding and Improving Layer Normalization. In Advances in Neural Information Processing Systems . 4383–4393
Jingjing Xu, Xu Sun, Zhiyuan Zhang, Guangxiang Zhao, and Junyang Lin. 2019 · 2019
Later among the works it cites.
FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine
Junlin Zhang, Tongwen Huang, and Zhiqi Zhang. 2019 · 2019
Later among the works it cites.
Rethinking Batch Normalization in Transformers
Sheng Shen, Zhewei Yao, Amir Gholami, Michael Mahoney, and Kurt Keutzer. 2020 · 2020
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