Maximum a posteriori estimation by search in probabilistic programs
We introduce an approximate search algorithm for fast maximum a posteriori probability estimation in probabilistic programs, which we call Bayesian ascent Monte Carlo (BaMC). Probabilistic programs represent probabilistic models with varying number of mutually dependent finite, countable, and contin...
Главные авторы: | Tolpin, D, Wood, F |
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Формат: | Conference item |
Опубликовано: |
AAAI Publications
2015
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