报告题目 (Title)：Estimating the number of clusters for high-dimensional mixture model(高维混合模型的聚类问题)
报告人 (Speaker)：刘一鸣 博士（暨南大学）
报告时间 (Time)：2021年11月7日(周日) 10：00
报告地点 (Place)：腾讯会议（会议号：926 463 645）
邀请人(Inviter)：张阳春
报告摘要：This paper proposes the variant Akaike and Bayesian information criteria to estimate the number of clusters for high dimensional mixture data. By investigating the limiting behaviours of the eigenvalues of sample covariance matrix for the observed data, the consistency of our criteria is obtained in different scenarios under some derived conditions. Simulation studies demonstrate that our approaches are more robust and competitive than other existing techniques.