1 INTRODUCTION

2 RELATED WORKS

3 INFLUENCE MAXIMIZATION

4 TRADITIONAL ALGORITHMS

5 DEEP REINFORCEMENT LEARNING FOR COMBINATORIAL OPTIMIZATION

6 ML-BASED INFLUENCE MAXIMIZATION ALGORITHMS

7 ML-BASED VARIANTS OF INFLUENCE MAXIMIZATION

8 RESEARCH CHALLENGES AND DIRECTIONS

9 CONCLUSION