2002 StochasticLambdaCalculusandMona

• (Ramsey & Pfeffer, 2002) ⇒ Norman Ramsey, and Avi Pfeffer. (2002). “Stochastic Lambda Calculus and Monads of Probability Distributions.” In: Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages. ISBN:1-58113-450-9 doi:10.1145/503272.503288

Subject Headings: Stochastic Lambda Calculus, Probabilistic Programming Language.

Cited By

• http://scholar.google.com/scholar?q=%222002%22+Stochastic+Lambda+Calculus+and+Monads+of+Probability+Distributions
• http://dl.acm.org/citation.cfm?id=503272.503288&preflayout=flat#citedby

Quotes

Abstract

Probability distributions are useful for expressing the meanings of probabilistic languages, which support formal modeling of and reasoning about uncertainty. Probability distributions form a monad, and the monadic definition leads to a simple, natural semantics for a stochastic lambda calculus, as well as simple, clean implementations of common queries. But the monadic implementation of the expectation query can be much less efficient than current best practices in probabilistic modeling. We therefore present a language of measure terms, which can not only denote discrete probability distributions but can also support the best known modeling techniques. We give a translation of stochastic lambda calculus into measure terms. Whether one translates into the probability monad or into measure terms, the results of the translations denote the same probability distribution.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2002 StochasticLambdaCalculusandMona	Avi Pfeffer Norman Ramsey			Stochastic Lambda Calculus and Monads of Probability Distributions				10.1145/503272.503288		2002