Lei Yang's paper "Noah: Neural-optimized A* Search Algorithm for Graph Edit Distance Computation" has been accepted by ICDE 2021, which is about optimizing traditional A* search algorithm by using graph neural networks.

Graph Edit Distance (GED) is a classical graph similarity metric that can be tailored to a wide range of applications. This paper proposes a novel approach Noah, which combines A* search algorithm and graph neural networks to compute approximate GED in a more effective and intelligent way. Specifically, it optimizes the search direction and reduces the search size of A* search algorithm. Experimental results demonstrate the practical effectiveness of our approach on several tasks and suggest that our approach significantly outperforms the state-of-the-art methods.