十大网投靠谱网站学术报告
Greedy Randomized Average Block Kaczmarz Method for Large Linear Systems
巫文婷
（北京理工大学数学与统计学院）
报告时间：2023年10月26日 星期四 下午 16：00-17:00
报告地点：沙河校区E404
报告摘要：Inspired by the greedy randomized Kaczmarz method, we propose a probability criterion which can capture subvectors of the residual whose norms are relatively large, constructing the greedy randomized average block Kaczmarz method for solving the consistent system of linear equations, which can be implemented in a distributed environment. When the size of each block is one, the probability criterion in the greedy randomized average block Kaczmarz method is a generalization of that in the greedy randomized Kaczmarz method. The experimental results show the advantage of the greedy randomized average block Kaczmarz method over the greedy randomized Kaczmarz method and several existing randomized block Kaczmarz methods.
报告人简介：巫文婷，中国科学院数学与系统科学研究院博士，北京理工大学数学与统计学院特别副研究员。研究方向为数值代数与科学计算，近年来主要从事随机迭代方法的相关研究。2019年获第七届中国数学会计算数学分会“应用数值代数奖”。担任Numerical Linear Algebra with Applications期刊编委。主持国家自然科学基金项目1项。
邀请人：谢家新，黄猛
