Work

A Learning based Branch and Bound for Maximum Common Subgraph Problems

Year: 2019

Type: preprint

Abstract: Branch-and-bound (BnB) algorithms are widely used to solve combinatorial problems, and the performance crucially depends on its branching heuristic.In this work, we consider a typical problem of maximum common subgraph (MCS), and propose a branching heuristic inspired from reinforcement learning with a goal of reaching a tree leaf as early as possible to greatly reduce the search tree size.Extensive experiments show that our method is beneficial and outperforms current best BnB algorithm for the MCS.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.1905.05840

Authors: Liu, Yan-li, Li, Chu-min, Jiang, Hua, He, Kun

Institutions: Wuhan University of Science and Technology, Huazhong University of Science and Technology, Université de Picardie Jules Verne

Language: English

Topic: Graph Theory and Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W2945358116

Cites: 16

Cited by: 2

Related to: 10