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Applications of the lasso and grouped lasso to the estimation of sparse graphical models
lasso and grouped lasso sparse graphical models
2015/8/21
We propose several methods for estimating edge-sparse and nodesparse graphical models based on lasso and grouped lasso penalties.We develop efficient algorithms for fitting these models when the numbe...
Learning the Structure of Deep Sparse Graphical Models
Structure Deep Sparse Graphical Models deep belief networks
2010/3/9
Deep belief networks are a powerful way to model complex probability
distributions. However, learning the structure of a belief network,
particularly one with hidden units, is difficult. The Indian...