Feature selection via sensitivity analysis of SVM probabilistic outputs

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Robust Large Margin Deep Neural Networks (2016, background): “neural networks [38], [39], and for the construction of radial basis function networks [40], since the spectral norm of the Jacobian matrix quantifies the sensitivity of DNN output with”
Feature Selection via Probabilistic Outputs (2012, methodology): “Conclusions In this paper, we have considered the feature scoring algorithm presented by Shen et al. (2008) and proposed our own related score for use in feature selection tasks.”
Feature Selection as a One-Player Game (2010, methodology): “These results are comparable to the state of the art along the NIPS FS challenge setting (using an additional separate test set): the best performance on Madelon (reached by (Shen et al., 2008)) is 6.”
An Effective Feature Selection Method via Mutual Information Estimation (2012, methodology): “The RP procedure [17]–[19] of a particular feature, feature j, is now described for a general data set D = {(xi, yi)}i=1.”