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Decentralized Graph Neural Network for Privacy-Preserving Recommendation
The first stage builds a local inner-item hypergraph for each user and a global inter-user graph.
Freshness or Accuracy, Why Not Both? Addressing Delayed Feedback via Dynamic Graph Neural Networks
In the model training, we propose a novel graph convolutional method named HLGCN, which leverages both high-pass and low-pass filters to deal with conversion and non-conversion relationships.
A multi view multi stage and multi window framework for pulmonary artery segmentation from CT scans
In addition, in order to improve the segmentation performance, we adopt multi-view and multi-window level method, at the same time we employ a fine-tune strategy to mitigate the impact of inconsistent labeling.
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