A method optimizes a predictive computation model efficiently. The method includes (i) selecting model parameters that are expected to take real values within a one-sided predetermined range; and (ii) 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 the examined model parameter attains or moves past a value that is idempotent to the computation model, removing the model parameter from the computation model. In one embodiment, the predetermined range is either the range between a predetermined positive real value and positive infinity or the range between a predetermined negative real value and negative infinity. The predetermined positive real value or the predetermined negative real value may be an idempotent value to the model computation.