Partial Routing As opposed to the entire output space on data sets, the sub-output space corresponding to individual examples is rather small, i.e., only few labels are assigned to one document in text classification, for example.
it is redundant to route low-level capsules to the entire output space for each example in the training stage, which motivated us to present a partial routing algorithm with constrained output spaces, such that our NAS function is described as: where D + and D − denote the sets of real (positive) and randomly selected (negative) outputs for each example, respectively.