Search Results for author: Xiang-Rong Sheng

Found 5 papers, 1 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

Joint Optimization of Ranking and Calibration with Contextualized Hybrid Model

no code implementations12 Aug 2022 Xiang-Rong Sheng, Jingyue Gao, Yueyao Cheng, Siran Yang, Shuguang Han, Hongbo Deng, Yuning Jiang, Jian Xu, Bo Zheng

To address this issue, we propose an approach that can Jointly optimize the Ranking and Calibration abilities (JRC for short).

Click-Through Rate Prediction

Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling

1 code implementation29 Apr 2021 Siyu Gu, Xiang-Rong Sheng, Ying Fan, Guorui Zhou, Xiaoqiang Zhu

If conversion happens outside the waiting window, this sample will be duplicated and ingested into the training pipeline with a positive label.

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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