Time varying undirected graphs

@article{Zhou2008TimeVU,
  title={Time varying undirected graphs},
  author={Shuheng Zhou and John D. Lafferty and Larry A. Wasserman},
  journal={Machine Learning},
  year={2008},
  volume={80},
  pages={295-319}
}
Undirected graphs are often used to describe high dimensional distributions. Under sparsity conditions, the graph can be estimated using ℓ 1 penalization methods. However, current methods assume that the data are independent and identically distributed. If the distribution, and hence the graph, evolves over time then the data are not longer identically distributed. In this paper we develop a nonparametric method for estimating time varying graphical structure for multivariate Gaussian… CONTINUE READING
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