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Xuanzhou Liu

2 accepted papers

2023

D2Match: Leveraging Deep Learning and Degeneracy for Subgraph Matching

ICML 2023poster

Subgraph matching is a fundamental building block for graph-based applications and is challenging due to its high-order combinatorial nature. Existing studies usually tackle it by combinatorial optimization or learning-based methods. However, they suffer from exponential computational costs or searc…

2023

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

ICML 2023poster

Neural architecture search (NAS) for Graph neural networks (GNNs), called NAS-GNNs, has achieved significant performance over manually designed GNN architectures. However, these methods inherit issues from the conventional NAS methods, such as high computational cost and optimization difficulty. Mor…