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