English

A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms

Artificial Intelligence 2024-03-18 v1 Disordered Systems and Neural Networks Data Structures and Algorithms Machine Learning Optimization and Control Quantum Physics

Abstract

This manuscript provides a comprehensive review of the Maximum Clique Problem, a computational problem that involves finding subsets of vertices in a graph that are all pairwise adjacent to each other. The manuscript covers in a simple way classical algorithms for solving the problem and includes a review of recent developments in graph neural networks and quantum algorithms. The review concludes with benchmarks for testing classical as well as new learning, and quantum algorithms.

Keywords

Cite

@article{arxiv.2403.09742,
  title  = {A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms},
  author = {Raffaele Marino and Lorenzo Buffoni and Bogdan Zavalnij},
  journal= {arXiv preprint arXiv:2403.09742},
  year   = {2024}
}

Comments

24 pages

R2 v1 2026-06-28T15:20:42.499Z