Stochastic Approximate Bayesian Inference Algorithm

A Stochastic Approximate Bayesian Inference Algorithm is an approximate bayesian inference algorithm (point estimator) that uses a sampling algorithm.

• AKA: Monte Carlo Inferencing, Sampling-based Inferencing.
• Context:
  • It can be implemented by a Stochastic Approximate Bayesian Inference System (that solve a Stochastic Approximate Bayesian Inference Task).
  • It can use a Monte Carlo Sampling Algorithm
• Example(s):
  • an MCMC Algorithm, such a Gibbs Sampling Algorithm.
  • Slice Sampling Algorithm. (Neal, 2003).
  • …
• Counter-Example(s):
  • Deterministic Approximate Bayesian Inference Algorithm.
• See: Point Estimator.

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