Figure 1.

A schematic representation of multi-task neural network. For each instance, a set of features and several class labels for the tasks are used for training. Input layer is followed by representation learning layers to learn the common representations, then followed by multiple classifiers to deal with the distinctions, after which an output layer is constructed for each classifier.