High-dimensional regression and classification under a class of convex loss functions
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Publication:897181
DOI10.4310/SII.2013.V6.N2.A11zbMATH Open1327.62404MaRDI QIDQ897181
Publication date: 17 December 2015
Published in: Statistics and Its Interface (Search for Journal in Brave)
Related Items (8)
Covariance-regularized regression and classification for high dimensional problems ⋮ Convex models of high dimensional discrete data ⋮ Modified Cheeger and ratio cut methods using the Ginzburg–Landau functional for classification of high-dimensional data ⋮ High dimensional binary classification under label shift: phase transition and regularization ⋮ Analysis to Neyman-Pearson classification with convex loss function ⋮ Title not available (Why is that?) ⋮ High-dimension multilabel problems: convex or nonconvex relaxation? ⋮ Classification with Gaussians and convex loss
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