IEEE

Combining Reinforcement Learning and Heuristic Optimization: A Model Based on a Deep Q-Network and Graph Neural Networks for Graph Coloring

Abstract: We present a hybrid approach combining Reinforcement Learning (RL) with the TabuCol, which is a version of tabu search specifically designed for the Graph Coloring Problem (GCP), enhanced by ...
IEEE

GLICE: Combining Graph Neural Networks and Program Slicing to Improve Software Vulnerability Detection

Abstract: This paper introduces the GLICE (Graph Neural Network with program slice) model for static code analysis to detect vulnerabilities in source code. GLICE combines inter-procedural program ...