2021.12.10 11:30 腾讯会议

The influence maximization problem, which asks for a small node set of maximum influence, is a key algorithmic problem in social influence analysis, and has been extensively studied over the past decade. It has wide applications to viral marketing, outbreak detection, rumor monitoring, etc. Most of the above results depends on the submodularity of the objective function. Moreover, the general problem of optimizing a submodular function subject to constraints captures many problems of interest both in theory and in practice, including maximum coverage, social welfare maximization, influence maximization in social networks, sensor placement, maximum cut, minimum cut, and facility location. In this talk, I will show several basic results in this area, and discuss some follow-up studies in recent years.