题目：Influence maximization and submodular optimization

报告人：刘彬，中国海洋大学数学科学学院副教授

报告时间：2020年9月26日下午 14:30-15：30

点击链接直接加入会议： https://meeting.tencent.com/s/pyXbZ7g3VMOS

腾讯会议 ID：287 217 416

摘要：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.

报告人简介：刘彬，中国海洋大学数学科学学院副教授。2010年毕业于山东大学运筹学与控制论专业，获理学博士学位。研究领域和兴趣：近似算法的设计与分析、社交网络、图论等。2016年作为访问学者赴美国德克萨斯大学达拉斯分校访问一年。在Journal of Global Optimization、Journal of Graph Theory、 Journal of Combinatorial Optimization、Science China: Mathematics等期刊和INFOCOM等会议发表论文40余篇。目前担任中国运筹学会数学规划分会青年理事，中国运筹学会图论组合学分会青年理事、副秘书长，美国数学会Mathematical Reviews评论员等。主持国家自然科学基金面上项目等科研项目共计8项。