Kernel Mean Shrinkage Estimators

21 May 2014Krikamol MuandetBharath SriperumbudurKenji FukumizuArthur GrettonBernhard Schölkopf

A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principal component analysis, and it also forms the core inference step of modern kernel methods that rely on embedding probability distributions in RKHSs. Given a finite sample, an empirical average has been used commonly as a standard estimator of the true kernel mean... (read more)

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