  Auxiliary Learning is a machine learning approach in which the model
acknowledges the existence of objects that do not come under any of its learned
categories.The name Auxiliary learning was chosen due to the introduction of an
auxiliary class. The paper focuses on increasing the generality of existing
narrow purpose neural networks and also highlights the need to handle unknown
objects. The Cat & Dog binary classifier is taken as an example throughout the
paper.
