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JMLR
2012
13 years 3 months ago
2012
We consider the sparse inverse covariance regularization problem or graphical lasso with regularization parameter λ. Suppose the sample covariance graph formed by thresholding th...
144
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JMLR
2012
13 years 3 months ago
2012
We study a generalized framework for structured sparsity. It extends the well known methods of Lasso and Group Lasso by incorporating additional constraints on the variables as pa...
137
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JMLR
2012
13 years 3 months ago
2012
The expectation maximization (EM) algorithm is a popular algorithm for parameter estimation in models with hidden variables. However, the algorithm has several non-trivial limitat...
122
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JMLR
2012
13 years 3 months ago
2012
We transform the outputs of each hidden neuron in a multi-layer perceptron network to have zero output and zero slope on average, and use separate shortcut connections to model th...
129
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JMLR
2012
13 years 3 months ago
2012
One approach to modeling structured discrete data is to describe the probability of states via an energy function and Gibbs distribution. A recurring difficulty in these models is...