I am reading a paper about a convex model for non-negative matrix factorization. In the paper it describes how to do such a technique and it says that it uses the augmented Lagrangian.
I can't find any really detailed information about the augmented lagrangian. Does any one know of any references, texts or maybe have an intuitive explanation of how the augmented lagrangian works and how it was derived?
Thank you for any help comments in advance.