The paper provides novel lower bounds connecting L1 distances of mixture densities to discrepancies in mixing measures, leading to first contraction rates for Dirichlet process mixtures with unknown scale.
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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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Convergence Rates for Latent Mixing Measures in Infinite Homoscedastic Location-Scale Mixture Models
The paper provides novel lower bounds connecting L1 distances of mixture densities to discrepancies in mixing measures, leading to first contraction rates for Dirichlet process mixtures with unknown scale.