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.
arXiv preprint arXiv:2503.24004
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Skew-Laplace approximation improves posterior density recovery for Dirichlet process mixtures by about 30 percent over standard Laplace and runs substantially faster than MCMC.
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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.
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Laplace and skew-Laplace approximations for Dirichlet process mixture posterior density
Skew-Laplace approximation improves posterior density recovery for Dirichlet process mixtures by about 30 percent over standard Laplace and runs substantially faster than MCMC.