Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting
Performing exact Bayesian inference for complex models is computationally intractable. Markov chain Monte Carlo (MCMC) algorithms can provide reliable approximations of the posterior distribution but are expensive for large data sets and high-dimensional models. A standard approach to mitigate this...
| Main Authors: | , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Journal of Machine Learning Research
2022
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