hi there today we'll look at mix-up beyond empirical risk minimization by a Hong Yi Chang Mustapha sis Yong and dolphin and David Lopes Pass so this paper is actually pretty simple but it introduces a technique that apparently helps with training classifiers and it I have it seen it used in practice so there must be at least something to it it is ultimately very simple so usually you input a data point X into your neural network in deep learning so f of X that's your neural network your known neural network has parameters