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2017年7月18日 Professor Ye, Xiaojing 学术报告
上传时间:2017-07-14 作者:杭电理学院 浏览次数:
报告题目:Influence Prediction for Continuous-Time Information Propagation on Networks
报告人:Professor Ye, Xiaojing
报告内容:
 

We consider the problem of predicting influence, defined as the expected number of infected nodes, resulted from information propagating from any given set of source nodes on a network. We develop a novel and transformative framework that adaptively aggregates the activation states of the network according to the number of active nodes, leading to the construction of a system of differential equations that governs the time evolution of the state probabilities. This system is analogous to theFokker-Planck equation in continuous space, and the solution readily yields the desired influence. This approach gives rise to a class of novel and scalable algorithms that work effectively for large-scale and dense networks. Numerical results on a variety of synthetic and real-world networks will be presented.

 
报告人简介:
   Ye, Xiaojing received B.S. in Mathematics in 2006 from Peking University, and M.S. in Statistics in 2009 and Ph.D. in Mathematics in 2011 both from the University of Florida, USA. He was a visiting assistant professor at Georgia Institute of Technology from August 2011 to July 2013 and has been assistant professor at Georgia State University since August 2013. His research focuses on mathematical modeling and computational methods for medical image recovery and optimization methods for big data problems.
报告时间: 2017年7月18日下午 15:00-16:00
报告地点:理学院学术报告厅(六教南528)
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