research
∙
09/04/2022
Towards Understanding the Overfitting Phenomenon of Deep Click-Through Rate Prediction Models
Deep learning techniques have been applied widely in industrial recommen...
share
research
∙
08/22/2022
KEEP: An Industrial Pre-Training Framework for Online Recommendation via Knowledge Extraction and Plugging
An industrial recommender system generally presents a hybrid list that c...
research
∙
11/11/2020
CAN: Revisiting Feature Co-Action for Click-Through Rate Prediction
Inspired by the success of deep learning, recent industrial Click-Throug...
research
∙
06/10/2020
Search-based User Interest Modeling with Lifelong Sequential Behavior Data for Click-Through Rate Prediction
Rich user behavior data has been proven to be of great value for click-t...
research
∙
09/26/2019