33 results on '"Yongchun Zhu"'
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2. Interest Clock: Time Perception in Real-Time Streaming Recommendation System.
3. Attacking Pre-trained Recommendation.
4. Modeling Dual Period-Varying Preferences for Takeaway Recommendation.
5. Learn over Past, Evolve for Future: Forecasting Temporal Trends for Fake News Detection.
6. Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning.
7. Exploiting User Comments for Early Detection of Fake News Prior to Users' Commenting.
8. Aligning Domain-specific Distribution and Classifier for Cross-domain Classification from Multiple Sources.
9. Generalizing to the Future: Mitigating Entity Bias in Fake News Detection.
10. Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection.
11. Improving Fake News Detection of Influential Domain via Domain- and Instance-Level Transfer.
12. Multi-view Multi-behavior Contrastive Learning in Recommendation.
13. MDFEND: Multi-domain Fake News Detection.
14. Selective Fairness in Recommendation via Prompts.
15. Zoom Out and Observe: News Environment Perception for Fake News Detection.
16. User-Centric Conversational Recommendation with Multi-Aspect User Modeling.
17. Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion.
18. Personalized Prompts for Sequential Recommendation.
19. Multi-Representation Adaptation Network for Cross-domain Image Classification.
20. Customized Conversational Recommender Systems.
21. Memory-Guided Multi-View Multi-Domain Fake News Detection.
22. Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising.
23. Combat Data Shift in Few-shot Learning with Knowledge Graph.
24. Personalized Transfer of User Preferences for Cross-domain Recommendation.
25. Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users.
26. Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising.
27. Deep Subdomain Adaptation Network for Image Classification.
28. Neural Hierarchical Factorization Machines for User's Event Sequence Analysis.
29. Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks.
30. Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection.
31. Graph Factorization Machines for Cross-Domain Recommendation.
32. Transfer Learning Toolkit: Primers and Benchmarks.
33. A Comprehensive Survey on Transfer Learning.
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