Is Akaike Information Criterion a kind of loss function? I guess it probably is, but just want a confirmation. Thanks! 
 A: From Wikipedia's Loss function: "In mathematical optimization, statistics, decision theory and machine learning, a loss function or cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some "cost" associated with the event. An optimization problem seeks to minimize a loss function. An objective function is either a loss function or its negative (sometimes called a reward function, a profit function, a utility function, a fitness function, etc.), in which case it is to be maximized."
On this site we have a good explanation for what AIC is. That is, ASSUMING the residuals are Gaussian, AIC is log-likelihood is given by: "$ \log(L(\theta)) =-\frac{|D|}{2}\log(2*\pi) -\frac{1}{2} \log(|K|) -\frac{1}{2}(x-\mu)^T K^{-1} (x-\mu)$, $K$ being the covariance structure of your model, $|D|$ being the number of points in your datasets, $\mu$ the mean response and obviously $x$ being your dependent variable.
More specifically AIC is calculated to be equal to $2k - 2 \log(L)$, where $k$ is the number of fixed effect in your model and $L$ your likelihood function [1]. It practically compares trade-off between variance($2k$) and bias ($2 \log(L)$) in your modelling assumptions. As such in your case it would compare two different log-likelihood structures when it came to the bias term. That is because when you calculate your log-likelihood practically you look at two terms:
A fit term, denoted by $-\frac{1}{2}(x-\mu)^T K^{-1} (x-\mu)$ and a complexity penalization term, denoted by $-\frac{1}{2} \log(|K|)$."
Although the fit term is not called a loss function per se, it is a loss function, because log likelihood is optimized to yield an AIC value, that is, a step left out in the explanation above, and which is probably not fully characterized for general residuals that do not agree with the given Gaussian assumption. That answers your question, yes, it is a loss function. What you didn't ask is whether AIC is good for anything.
