MALA-within-Gibbs samplers can achieve dimension-independent acceptance and convergence rates for high-dimensional targets with sparse conditional structure, under block-wise log-concavity.
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MALA-within-Gibbs samplers for high-dimensional distributions with sparse conditional structure
MALA-within-Gibbs samplers can achieve dimension-independent acceptance and convergence rates for high-dimensional targets with sparse conditional structure, under block-wise log-concavity.