Clustering A Collection Of Networks With Mixtures Of L1-Sparse Graphical Models
Zuogong Yue, Victor Solo
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Attention has turned in recently to clustering of collections networks where each network is characterized by a sparse inverse covariance matrix. Here we consider a mixture model of sparse Gaussian graphical models and develop an exact EM algorithm that improves considerably on a previous approximation. We provide numerical examples to show its superior performance.
Chairs:
Zhanyu Ma