Search Results for author: Yujing Zhang

Found 4 papers, 0 papers with code

Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models

no code implementations4 Sep 2022 Zhao-Yu Zhang, Xiang-Rong Sheng, Yujing Zhang, Biye Jiang, Shuguang Han, Hongbo Deng, Bo Zheng

However, far less attention has been paid to the overfitting problem of models in recommendation systems, which, on the contrary, is recognized as a critical issue for deep neural networks.

Click-Through Rate Prediction Recommendation Systems

KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging

no code implementations22 Aug 2022 Yujing Zhang, Zhangming Chan, Shuhao Xu, Weijie Bian, Shuguang Han, Hongbo Deng, Bo Zheng

To alleviate this issue, we propose to extract knowledge from the \textit{super-domain} that contains web-scale and long-time impression data, and further assist the online recommendation task (downstream task).

Recommendation Systems

CAN: Feature Co-Action for Click-Through Rate Prediction

no code implementations11 Nov 2020 Weijie Bian, Kailun Wu, Lejian Ren, Qi Pi, Yujing Zhang, Can Xiao, Xiang-Rong Sheng, Yong-Nan Zhu, Zhangming Chan, Na Mou, Xinchen Luo, Shiming Xiang, Guorui Zhou, Xiaoqiang Zhu, Hongbo Deng

For example, a simple attempt to learn the combination of feature A and feature B <A, B> as the explicit cartesian product representation of new features can outperform previous implicit feature interaction models including factorization machine (FM)-based models and their variations.

Click-Through Rate Prediction

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