A Reference for PAC-Bayesian? I've recently came across topic known as PAC-Bayesian, but I cannot find a source to read about it. Any article that I came across are talking about its application in a specific area but there is no introduction to what it exactly is. 
 A: Here are a few quick Google hits...


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*PAC-Bayes Analysis: Background and
Applications

*Probably Approximately Correct Learning and Vapnik-Chervonenkis Dimension

*Probably approximately correct learning on Wikipedia

*Overview of the Probably Approximately Correct (PAC) Learning Framework
From this last one, a quote:

A more refined, Bayesian extension of the PAC model is explored in [26]. Using the Bayesian approach involves assuming a prior distribution over possible target concepts as well as training instances. Given these distributions, the average error of the hypothesis as a function of training sample size, and even as a function of the particular training sample, can be defined. Also, $1 - \delta$ confidence intervals like those in the PAC model can be defined as well.

[26] $=$ W. Buntine, A Theory of Learning Classification Rules. PhD thesis, University of Technology, Sydney, 1990.
A: This paper is a good way to start : https://arxiv.org/pdf/1901.05353.pdf
A: A more recent elementary introduction to PAC-Bayes
User-friendly introduction to PAC-Bayes bounds
by Pierre Alquier. It is an 80 page study of this topic.
