时间：2017年9月13（星期三）15：00-16：30

地点：学院南路校区，主教110

报告一题目：使用联合矩阵分解探测符号网络中的社团结构

报告人：中央财经大学统计与数学学院、张忠元教授

摘要：针对符号网络，即包含正边和负边的复杂网络的研究已经成为一个热点问题。探测符号网络中的社团结构对于理解符号网络的拓扑性质和功能有重要意义。我们提出联合矩阵分解模型用于探测符号网络中的社团结构。此模型和随机块模型与潜在语义分析模型有深刻的联系。数值实验验证了此模型的有效性。

报告二题目：On preconditioned iterative methods for saddle point problems from time-harmonic eddy current models

报告人：中央财经大学统计与数学学院、任志茹副教授

摘要：For the saddle point problem arising from the finite element discretization of the hybrid formulation of the time-harmonic eddy current problem, we propose an alternating positive semidefinite splitting preconditioner which is based on two positive semidefinite splittings of the saddle point matrix. It is proved that the corresponding alternating positive semidefinite splitting iteration method is unconditionally convergent. We show that the new preconditioner is much easier to implement than the block alternating splitting implicit preconditioner when they are used to accelerate the convergence rate of Krylov subspace methods such as GMRES. Numerical examples are given to show the effectiveness of our proposed preconditioner.