1. In an optimizing predictive computation model, a method comprising: selecting model parameters that are expected to take real values within a predetermined range; and iteratively: (a) receiving a set of input values; (b) executing the computation model based on the input values; (c) updating the values of the model parameters to minimize a loss function; and (d) examining each of the model parameters, such that, when an examined model parameter attains a value that is idempotent to the computation model, or passes through such a value during updating, or reaches a forbidden state, removing the examined model parameter and computations involving the examined model parameter from the computation model.