Shaozhen Ma

Towards Unsupervised Training of Matching-based Graph Edit Distance Solver via Preference-aware GAN

Graph Edit Distance (GED) is a fundamental graph similarity metric widely used in various applications. However, computing GED is an NP-hard problem. Recent state-of-the-art hybrid GED solver has shown promising performance by formulating GED as a bipartite graph matching problem, then leveraging a…