Imperial College London > Talks@ee.imperial > CAS Talks > Semantics of higher-order probabilistic programs

Semantics of higher-order probabilistic programs

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We present a semantics, that is to say an interpretation, of higher-order probabilistic programs in terms of linear operators between Banach spaces. Our semantics is rooted in the classical theory of Banach spaces and their tensor products, but bears similarities with the well-known Scott semantics of higher-order programs through the use ordered Banach spaces. In particular we can interpret fixpoints such as while loops. The central role of tensor products reflects the fact that our semantics treats randomness as a resource, e.g. probabilistic states cannot be copied. We illustrate the simplicity of working with linear operators by giving a simple proof of the validity of the Gibbs sampling algorithm.

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