On the Computability of Conditional Probability

As inductive inference and machine-learning methods in computer science see continued success, researchers are aiming to describe ever more complex probabilistic models and inference algorithms. It is natural to ask whether there is a universal computational procedure for probabilistic inference. We...

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Veröffentlicht in:	Journal of the ACM 2019-06, Vol.66 (3), p.1-40, Article 23
Hauptverfasser:	Ackerman, Nathanael L., Freer, Cameron E., Roy, Daniel M.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Bayesian analysis Conditional probability Machine learning Mathematics of computing Models of computation Probabilistic computation Probabilistic inference Probabilistic models Probability and statistics Probability theory Random variables Statistical analysis Theory of computation
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