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Hamiltonian Monte Carlo acceleration using surrogate functions with random bases
For big data analysis, high computational cost for Bayesian methods often limits their applications in practice. In recent years, there have been many attempts to improve computational efficiency of Bayesian inference. Here we propose an efficient and scalable computational technique for a state-of-...
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| 出版年: | Stat Comput |
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| 主要な著者: | , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
2016
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5624739/ https://ncbi.nlm.nih.gov/pubmed/28983154 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s11222-016-9699-1 |
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