PRx combines kernel weight localization with predictive recursion for fast semiparametric density regression, yielding consistent estimators for unmixed parameters and competitive performance at low computational cost.
The Annals of Probability , pages=
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Bayesian softmax-gated mixture-of-experts models achieve posterior contraction for density estimation and parameter recovery using Voronoi losses, plus two strategies for choosing the number of experts.
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Fast Semiparametric Density Regression with Weight-localized Predictive Recursion
PRx combines kernel weight localization with predictive recursion for fast semiparametric density regression, yielding consistent estimators for unmixed parameters and competitive performance at low computational cost.
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On Bayesian Softmax-Gated Mixture-of-Experts Models
Bayesian softmax-gated mixture-of-experts models achieve posterior contraction for density estimation and parameter recovery using Voronoi losses, plus two strategies for choosing the number of experts.