I am reading __A Tutorial on Energy Based-Learning__ and I am trying to understand the difference between all those terms stated above in the context of SVMs. This __link__ summarizes the differences between a loss, cost, and an objective function. Based on my understanding,

**Objective function**: Something we want to minimize. For example ||w||^2 for SVM.

**Loss function**: Penalty between prediction and label which is also equivalent to the regularization term. An example is the hinge loss function in SVM.

**Cost function**: A general formulation that combines the objective and loss function.

Now, the 1st link states that the hinge function is max(0, m + E(W,Yi,Xi) - E(W,Y,X)) i.e. it is a function of the energy term. Does that mean that the energy function of the SVM is 1 - y(wx + b)? Are energy functions are a part of a loss function. And a loss + objective function a part of the cost function?

A concise summary of the 4 terms would immensely help my understanding. Also, do correct me if my understanding is wrong. The terms sound so confusing. Thanks!