Recursively enumerable sets and degrees
Recursively enumerable sets and degrees
Theory of recursive functions and effective computability
Theory of recursive functions and effective computability
A probabilistic powerdomain of evaluations
Proceedings of the Fourth Annual Symposium on Logic in computer science
Selected papers of the workshop on Topology and completion in semantics
Computability on random variables
Theoretical Computer Science - Special issue on computability and complexity in analysis
Computability on the probability measures on the Borel sets of the unit interval
Theoretical Computer Science - Special issue on computability and complexity in analysis
Computable analysis: an introduction
Computable analysis: an introduction
Stochastic lambda calculus and monads of probability distributions
POPL '02 Proceedings of the 29th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
The Scott Topology Induces the Weak Topology
LICS '96 Proceedings of the 11th Annual IEEE Symposium on Logic in Computer Science
Representing probability measures using probabilistic processes
Journal of Complexity
Borel Complexity of Topological Operations on Computable Metric Spaces
CiE '07 Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World
A probabilistic language based on sampling functions
ACM Transactions on Programming Languages and Systems (TOPLAS)
Learning systems of concepts with an infinite relational model
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
IBAL: a probabilistic rational programming language
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Natively probabilistic computation
Natively probabilistic computation
Randomness and the ergodic decomposition
CiE'11 Proceedings of the 7th conference on Models of computation in context: computability in Europe
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We prove a uniformly computable version of de Finetti's theorem on exchangeable sequences of real random variables. In the process, we develop machinery for computably recovering a distribution from its sequence of moments, which suffices to prove the theorem in the case of (almost surely) continuous directing random measures. In the general case, we give a proof inspired by a randomized algorithm which succeeds with probability one. Finally, we show how, as a consequence of the main theorem, exchangeable stochastic processes in probabilistic functional programming languages can be rewritten as procedures that do not use mutation.