Which ANN structure to use? Let $\mathcal{S}$ be the training input data set where each input $u^i \in \mathcal{S}$  has $d$ features.
I want to design a ANN so that the cost function below is minimized (the sum of
square of pairwise differences between model outputs)  and the given constraint is satisfied, where $w$ is ANN model parameter vector.

Question: what kind of ANN is suitable for this purpose?[
A Siamese network (a network with multiple outputs) will work for such a case.