• Could using a heteroskedastic noise assumption improve the performance of the sizereparameterized search space? 14 14 The objective function may be subject to heteroskedastic noise. In the limit of infinite particles, it seems likely that the variance of repeat sampling from the objective function for a fixed set of parameters will tend towards zero. Treatment of heteroskedastic noise is a promising avenue for future work, since heteroskedastic noise may be (at least one) reason for the surprising behavior for a few of the search space combinations. One way this can be implemented is by specifying the standard deviation (SEM in Ax terms) of repeat observations directly or using a model that infers heteroskedastic noise (see e.g., and )