A Predicate/State Transformer Semantics for Bayesian Learning
نویسندگان
چکیده
This paper establishes a link between Bayesian inference (learning) and predicate and state transformer operations from programming semantics and logic. Specifically, a very general definition of backward inference is given via first applying a predicate transformer and then conditioning. Analogously, forward inference involves first conditioning and then applying a state transformer. These definitions are illustrated in many examples in discrete and continuous probability theory and also in quantum theory.
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ورودعنوان ژورنال:
- Electr. Notes Theor. Comput. Sci.
دوره 325 شماره
صفحات -
تاریخ انتشار 2016