Research map / Label-efficient and robust learning / Recognition and long-tail
Multi-Feature Discrete Collaborative Filtering for Fast Cold-Start Recommendation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use MFDCF instead of DDL | MovieLens-1M cold-start recommendation · MovieLens-1M | training time: about 50 times faster | Helped |
| Use MFDCF instead of DFM | MovieLens-1M cold-start recommendation · MovieLens-1M | training time: about 3 times faster | Helped |
Closest papers by meaning
- Discrete Personalized Ranking for Fast Collaborative Filtering from Implicit Feedback (AAAI 2017 · similarity 0.89)
- Temporally and Distributionally Robust Optimization for Cold-Start Recommendation (AAAI 2024 · similarity 0.87)
- Optimizing Recall in Deep Graph Hashing Framework for Item Retrieval (Student Abstract) (AAAI 2024 · similarity 0.85)
- Preference Aware Dual Contrastive Learning for Item Cold-Start Recommendation (AAAI 2024 · similarity 0.84)
- From Pairwise to Ranking: Climbing the Ladder to Ideal Collaborative Filtering with Pseudo-Ranking (AAAI 2025 · similarity 0.83)
- Feature-Structure Adaptive Completion Graph Neural Network for Cold-start Recommendation (AAAI 2025 · similarity 0.83)
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