228 citations · 392 across the 12 of their papers we have counts for
3 papers · 1 filter
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow
Yuling Yan, Kaizheng Wang, Philippe Rigollet
Gaussian mixture models form a flexible and expressive parametric family of distributions that has found applications in a wide variety of applications. Unfortunately, fitting thes…
An theory of PCA and spectral clustering
Emmanuel Abbe, Jianqing Fan, Kaizheng Wang
Principal Component Analysis (PCA) is a powerful tool in statistics and machine learning. While existing study of PCA focuses on the recovery of principal components and their asso…
Entrywise Eigenvector Analysis of Random Matrices with Low Expected Rank
Emmanuel Abbe, Jianqing Fan, Kaizheng Wang +1
Recovering low-rank structures via eigenvector perturbation analysis is a common problem in statistical machine learning, such as in factor analysis, community detection, ranking,…