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Found 2 papers, 2 papers with code
Lightweight Embeddings for Graph Collaborative Filtering
Graph neural networks (GNNs) are currently one of the most performant collaborative filtering methods.
Learning Compact Compositional Embeddings via Regularized Pruning for Recommendation
In addition, we innovatively design a regularized pruning mechanism in CERP, such that the two sparsified meta-embedding tables are encouraged to encode information that is mutually complementary.
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