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Discussion of “Latent Variable Graphical Model Selection via Convex Optimization”
Latent Variable Graphical Model Selection Convex Optimization
2015/6/17
We wish to congratulate the authors for their innovative contribution, which is bound to inspire much further research. We find latent variable model selection to be a fantastic application of matrix ...
This paper studies the partial estimation of Gaussian graphical models from high-dimensional empirical observations. We derive a convex formulation for this problem using $\ell_1$-regularized maximum-...
High-Dimensional Gaussian Graphical Model Selection: Tractable Graph Families
Gaussian graphical model selection high-dimensional learning local-separation property walk-summability
2011/9/29
Abstract: We consider the problem of high-dimensional Gaussian graphical model selection. We identify a set of graphs for which an efficient estimation algorithm exists, and this algorithm is based on...