Density-sensitive semisupervised inference

7 Apr 2012 Martin Azizyan Aarti Singh Larry Wasserman

Semisupervised methods are techniques for using labeled data $(X_1,Y_1),\ldots,(X_n,Y_n)$ together with unlabeled data $X_{n+1},\ldots,X_N$ to make predictions. These methods invoke some assumptions that link the marginal distribution $P_X$ of X to the regression function f(x)... (read more)

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