• Corpus ID: 246035994

Continual Learning for CTR Prediction: A Hybrid Approach

@article{Hu2022ContinualLF,
  title={Continual Learning for CTR Prediction: A Hybrid Approach},
  author={Ke Hu and Yi Qi and Jianqiang Huang and Jia Cheng and Jun Lei},
  journal={ArXiv},
  year={2022},
  volume={abs/2201.06886}
}
Click-through rate(CTR) prediction is a core task in cost-perclick(CPC) advertising systems and has been studied extensively by machine learning practitioners. While many existing methods have been successfully deployed in practice, most of them are built upon i.i.d.(independent and identically distributed) assumption, ignoring that the click data used for training and inference is collected through time and is intrinsically non-stationary and drifting. This mismatch will inevitably lead to sub… 
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