报告人：姜铁峰
报告地点：数学与统计学院415会议室
报告时间：2020年01月04日星期六09:40-10:40
报告摘要：
Consider a standard white Wishart matrix with parameter n and p. Motivated by applications in high-dimensional statistics and signal processing, we perform asymptotic analysis on the maxima and minima of the eigenvalues of all the m by m principal minors, under the asymptotic regime that n, p, m go to infinity. Asymptotic results concerning extreme eigenvalues of principal minors of real Wigner matrices are also obtained. In addition, we discuss an application of the theoretical results to the construction of compressed sensing matrices, which provides insights in high dimensional linear regression.
主讲人简介：
姜铁峰，现为明尼苏达大学教授，于吉林大学数学学院获得学士学位，斯坦福大学获得统计学博士学位，主要研究方向为随机矩阵、随机图、概率论和高维统计推断。
