Sparsistent Estimation of Time-Varying Discrete Markov Random Fields

14 Jul 2009 Mladen Kolar Eric P. Xing

Network models have been popular for modeling and representing complex relationships and dependencies between observed variables. When data comes from a dynamic stochastic process, a single static network model cannot adequately capture transient dependencies, such as, gene regulatory dependencies throughout a developmental cycle of an organism... (read more)

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