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作者答复：通过凸优化选择潜变量图模型AI 解读

Introduction.We thank all the discussants for their careful reading of our paper, and for their insightful critiques.We would also like to thank the editors for organizing this discussion.Our paper contributes to the area of high-dimensional statistics which has received much attention over the past several years across the statistics, machine learning and signal processing communities.In this rejoinder we clarify and comment on some of the points raised in the…

通过凸优化选择潜变量图模型AI 解读

Suppose we observe samples of a subset of a collection of random variables. No additional information is provided about the number of latent variables, nor of the relationship between the latent and observed variables. Is it possible to discover the number of latent components, and to learn a statistical model over the entire collection of variables? We address this question in the setting in which the latent and observed variables are jointly Gaussian, with the conditional…