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Found 6 papers, 2 papers with code
Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
With the increase in the business scale and number of domains in online advertising, multi-domain ad recommendation has become a mainstream solution in the industry.
Confidence-Aware Multi-Field Model Calibration
Accurately predicting the probabilities of user feedback, such as clicks and conversions, is critical for advertisement ranking and bidding.
Making the Full Model Adaptive: Multi-level Domain Adaptation for Multi-Domain CTR Prediction
We then select them in a domain-aware way to promote informative features for different domains.
Unbiased Delayed Feedback Label Correction for Conversion Rate Prediction
To directly introduce the correct feedback label information, we propose an Unbiased delayed feedback Label Correction framework (ULC), which uses an auxiliary model to correct labels for observed negative feedback samples.
Contrastive Multi-view Framework for Customer Lifetime Value Prediction
Accurate customer lifetime value (LTV) prediction can help service providers optimize their marketing policies in customer-centric applications.
UNBERT: User-News Matching BERT for News Recommendation
Nowadays, news recommendation has become a popular channel for users to access news of their interests.
