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- research-articleJune 2024
LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 177, Pages 1–24https://doi.org/10.1145/3657302Graph collaborative filtering (GCF) has achieved exciting recommendation performance with its ability to aggregate high-order graph structure information. Recently, contrastive learning (CL) has been incorporated into GCF to alleviate data sparsity and ...
- research-articleJune 2024
Toward Few-Label Vertical Federated Learning
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 176, Pages 1–21https://doi.org/10.1145/3656344Federated Learning (FL) provides a novel paradigm for privacy-preserving machine learning, enabling multiple clients to collaborate on model training without sharing private data. To handle multi-source heterogeneous data, Vertical Federated Learning (VFL)...
- research-articleJune 2024
Mixed Graph Contrastive Network for Semi-supervised Node Classification
ACM Transactions on Knowledge Discovery from Data (TKDD), Volume 18, Issue 7Article No.: 162, Pages 1–19https://doi.org/10.1145/3641549Graph Neural Networks (GNNs) have achieved promising performance in semi-supervised node classification in recent years. However, the problem of insufficient supervision, together with representation collapse, largely limits the performance of the GNNs in ...