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Found 4 papers, 1 papers with code
Sparse Attentive Memory Network for Click-through Rate Prediction with Long Sequences
SAM supports efficient training and real-time inference for user behavior sequences with lengths on the scale of thousands.
Iterative Memory Network for Long Sequential User Behavior Modeling in Recommender Systems
Extensive empirical studies show that our method outperforms various state-of-the-art sequential modeling methods on both public and industrial datasets for long sequential user behavior modeling.
Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge
On the other hand, there is a large semantic gap between seen and unseen classes in the existing multi-label classification datasets.
Deep Time-Stream Framework for Click-Through Rate Prediction by Tracking Interest Evolution
Click-through rate (CTR) prediction is an essential task in industrial applications such as video recommendation.
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