Discussion: Latent variable graphical model selection via convex optimization

TL;DR

This paper discusses the approach of selecting latent variable graphical models using convex optimization techniques, highlighting the theoretical foundations and potential advantages of this method.

Contribution

It provides a detailed discussion on the convex optimization framework for latent variable graphical model selection, emphasizing its theoretical basis and practical implications.

Findings

Convex optimization offers a promising approach for latent variable model selection.

The method can effectively identify underlying graphical structures.

The discussion highlights potential advantages over traditional methods.

Abstract

Discussion of "Latent variable graphical model selection via convex optimization" by Venkat Chandrasekaran, Pablo A. Parrilo and Alan S. Willsky [arXiv:1008.1290].