报告人简介：
Dr. My T. Thai is a UF Research Foundation Professor and Nelms Endowed Professor in the Department of Computer and Information Sciences and Engineering at the University of Florida. Her current research interests include scalable machine learning, blockchain, cybersecurity, algorithms and optimization on network science and engineering, including communication networks, smart grids, social networks, and their interdependency. The results of her work have led to 6 books and 140+ articles, including IEEE MSN 2014 Best Paper Award, IEEE ICDCS 2017 Best Paper Runner Up, 2017 IEEE ICDM Best Papers Award, and 2018 IEEE ASONAM Best Paper Runner Up.
Dr. Thai has engaged in many professional activities. She currently serves as the EiC of the Computational Social Networks journal. She is also the founding and steering chair of the international conference on Computational Data and Social Networks. She has served as editors for several journal editorial boards, and also chaired or served on numerous program committees of international conferences and workshops. She has received many research awards including an UFRF Professorship Award, IoT Term Professorship, a Department of Defense (DoD) Young Investigator Award, and an NSF (National Science Foundation) CAREER Award.
报告内容简介：
One of the most fundamental problems in viral marketing is Influence Maximization (IM), which seeks to find a set of k initial seed users in a network so as to maximize the size of influenced users. Despite the huge amount of efforts, IM in billion-scale networks such as Facebook, Twitter, and Friendster has not been satisfactorily solved. In this talk, I will discuss a long road to achieve a quasi-linear time algorithm while guaranteeing the best approximation ratio (1 - 1/e - ε) to the IM problem. I will further present the latest exciting results, almost optimally solving the IM problem with a ratio of (1 - ε) on billion-scale networks. Finally, open challenges in actively doing viral marketing thru social influences will be discussed.
报告语言：英语