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Expectation Propagation for Neural Networks with Sparsity-promoting Priors
expectation propagation neural network multilayer perceptron linear model sparse prior automatic relevance determination
2013/4/28
We propose a novel approach for nonlinear regression using a two-layer neural network (NN) model structure with sparsity-favoring hierarchical priors on the network weights. We present an expectation ...
On false discovery rate thresholding for classification under sparsity
false discovery rate thresholding classification under sparsity
2011/7/6
We study the properties of false discovery rate (FDR) thresholding, viewed as a classification procedure. The "0"-class (null) is assumed to have a known, symmetric log-concave density while the "1"-c...
Structured Sparsity via Alternating Directions Methods
structured sparsity overlapping Group Lasso alternating directions methods variable splitting augmented Lagrangian
2011/6/21
We consider a class of sparse learning problems in high dimensional feature space regularized
by a structured sparsity-inducing norm which incorporates prior knowledge of the group
structure of the ...