Abstract: Graph neural networks provide a powerful frame-work for recommendation systems by capturing dependencies through message passing and modeling user-item interactions using an adjacency matrix ...
Abstract: Subgraph matching is a core primitive in graph analytics, yet it remains difficult to scale due to its combinatorial complexity and highly irregular memory access patterns. Despite decades ...
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