Admissibility as a Touchstone

By A. Mandelbaum, L. Shepp. 1987

Citations in the corpus

• Kernel Mean Embedding of Distributions: A Review and Beyonds (2016, methodology): “and a generative mean map kernel (GMMK) proposed by Mehta and Gray (2010). In the GMMK, the kernel between two objects x and y is defined via p̂x and p̂y, which are estimated probabilistic models of x and y, respectively.”
• Kernel Mean Shrinkage Estimators (2014, methodology): “A direct generalization of James-Stein estimator to infinite-dimensional Hilbert space has been considered, for example, in Berger and Wolpert (1983); Mandelbaum and Shepp (1987); Privault and Rveillac (2008).”
• Kernel Mean Estimation and Stein's Effect (2013, neutral): “Although some attempts have been made to understand this phenomenon in the infinite-dimensional space [17, 18, 19], this work presents a key challenge: the true probability distribution of μP is essentially unknown and is subject to the choice of kernel k and distribution P, whereas all the previous”