Kernel Mean Estimation via Spectral Filtering Kernel Mean Estimation via Spectral Filtering
Paper summary The paper presents a family of kernel mean shrinkage estimators. These estimators generalize the ones proposed in \cite{journals/jmlr/FukumizuSG13} and can incoporate useful domain knowledge through spetral filters. Here is a summary of interesting contributions: 1. Theorem 1 that shows the consistency and admissibility of kmse presented in \cite{journals/jmlr/FukumizuSG13}. 2. The idea of spectral kmse (its use in this unsupervised setting) and similarity of final form with the supervised setting. 3. Theorem 5 that shows consistency of the proposed spectral kmse.

Summary by NIPS Conference Reviews 5 years ago
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