Some suggestions

Hi Ricky,

Thanks for your informative page. I learned so many things.

Just a few things came into my mind about your page:

1. The abstract is too short and is not a clear summary of the wiki page.

2. You explain MCMC from machine learning point of view, not artificial intelligence. I expected this page to be explained on graphical models. For example to have a graph with large tree width and show how to do approximate inference on that using MCMC approaches.

3. There are a few references with no citations in the text. Also, there are some parts like the algorithms that need to be cited.

Cheers,

Bahare

Hi Bahare,

1. I'll update the abstract to contain more specifics.

2. True. But talking about graphical models probably requires another page. Instead, the Gibbs sampler is the most basic MCMC tool used for sampling from graphical models.

3. I'll add more citations to some specific claims.

Thanks,

Ricky