315 citations · 374 across the 5 of their papers we have counts for
5 papers
Continual Learning for CTR Prediction: A Hybrid Approach
Ke Hu, Yi Qi, Jianqiang Huang +2
Click-through rate(CTR) prediction is a core task in cost-per-click(CPC) advertising systems and has been studied extensively by machine learning practitioners. While many existing…
AutoSmart: An Efficient and Automatic Machine Learning framework for Temporal Relational Data
Zhipeng Luo, Zhixing He, Jin Wang +4
Temporal relational data, perhaps the most commonly used data type in industrial machine learning applications, needs labor-intensive feature engineering and data analyzing for giv…
Deep Position-wise Interaction Network for CTR Prediction
Jianqiang Huang, Ke Hu, Qingtao Tang +4
Click-through rate (CTR) prediction plays an important role in online advertising and recommender systems. In practice, the training of CTR models depends on click data which is in…
Neural News Recommendation with Attentive Multi-View Learning
Chuhan Wu, Fangzhao Wu, Mingxiao An +3
Personalized news recommendation is very important for online news platforms to help users find interested news and improve user experience. News and user representation learning i…
NPA: Neural News Recommendation with Personalized Attention
Chuhan Wu, Fangzhao Wu, Mingxiao An +3
News recommendation is very important to help users find interested news and alleviate information overload. Different users usually have different interests and the same user may…