Title（题目）Estimation of high dimensional inverse covariance matrix Speaker（报告人）Dr. Liu Weidong, from University of Pennsylvania, USA Time（时间）2010年12月15日（周三）下午3:00-4:00 Place（地点）北京大学理科一号楼1418教室 Abstract（摘要）In this presentation, I will talk about the estimation of sparse inverse covariance matrices. A constrained l1 minimization method is proposed for estimating a sparse inverse covariance matrix. The resulting estimator is shown to enjoy a number of desirable properties. In particular, it is shown that the rate of convergence between the estimator and the true s-sparse precision matrix under the spectral norm is s(log( p/n))1/2 when the population distribution has either exponential-type tails or polynomial-type tails. Convergence rates under the elementwise l∞ norm and Frobenius norm are also presented. In addition, graphical model selection is considered. The procedure is easily implementable by linear programming. Numerical performance of the estimator is investigated. 北京大学统计科学中心 |