Maximum a posteriori estimation by search in probabilistic programs

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...

書誌詳細
主要な著者:	Tolpin, D, Wood, F
フォーマット:	Conference item
出版事項:	AAAI Publications 2015

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