I don't know of any references, most of this is just stuff that falls out pretty easily once you try and do the math, and that's probably faster than reading a book.

I.e., set up maximal likelihood, take logs, and you immediately get least squares for g(x) a gaussian. If g(x)=exp(-|x|), you get l1 minimization. Other distributions give you other things.

The general topic to investigate is robust regression: https://en.wikipedia.org/wiki/Robust_regression