59 citations · 85 across the 7 of their papers we have counts for
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cs.IR2022★ 5 cited
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
Zhao-Yu Zhang, Xiang-Rong Sheng, Yujing Zhang +4
Deep learning techniques have been applied widely in industrial recommendation systems. However, far less attention has been paid to the overfitting problem of models in recommenda…
cs.IR2022★ 1 cited
KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging
Yujing Zhang, Zhangming Chan, Shuhao Xu +4
An industrial recommender system generally presents a hybrid list that contains results from multiple subsystems. In practice, each subsystem is optimized with its own feedback dat…
cs.IR2022
Approximate Nearest Neighbor Search under Neural Similarity Metric for Large-Scale Recommendation
Rihan Chen, Bin Liu, Han Zhu +8
Model-based methods for recommender systems have been studied extensively for years. Modern recommender systems usually resort to 1) representation learning models which define use…