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On l2 Error Bounds of the Elastic Net when p>>n
Lasso naive Elastic Net Elastic Net model selection consistency estimation consistency
2016/1/20
We study the estimation property of the Elastic Net in high-dimensional settings where the number of parameters p is comparable to or larger than the sample size n. In such a situation one often assum...
Dependent Dirichlet Priors and Optimal Linear Estimators for Belief Net Parameters
Dependent Dirichlet Priors Optimal Linear Estimators Belief Net Parameters
2012/9/19
A Bayesian belief network is a model of a joint distribution over a finite set of vari-ables, with a DAG structure representing im-mediate dependencies among the variables.For each node, a table of pa...
In the literature surrounding Bayesian penalized regression, the two primary choices of
prior distribution on the regression coecients are zero-mean Gaussian and Laplace. While
both have been compa...
Exact distribution theory for belief net responses
Bayesian network BDeprior belief network beta distribution query response
2009/9/22
Bayesian belief networks provide estimates of conditional probabilities,
called query responses. The precision of these estimates is assessed using posterior
distributions. This paper discusses two ...