An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem

• Published in: arXiv.org
• Main Authors: Liu, Huaiyuan, Liu, Xianzhang, Yang, Donghua, Wang, Hongzhi, Long, Yingchi, Ji, Mengtong, Miao, Dongjing, Liang, Zhiyu
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 16.08.2024
• Subjects: Apexes; Combinatorial analysis; Computer Science - Artificial Intelligence; Computer Science - Learning; Graph neural networks; Graph theory; Heuristic; Machine learning; Solvers; Unsupervised learning

The Maximum Minimal Cut Problem (MMCP), a NP-hard combinatorial optimization (CO) problem, has not received much attention due to the demanding and challenging bi-connectivity constraint. Moreover, as a CO problem, it is also a daunting task for machine learning, especially without labeled instances...