Algorithms that combat the curse of dimensionality take advantage of nonuniformity properties of the underlying functions, which may be rotational (e.g., grid alignment) or translational (e.g., near-singularities localized at certain points of the domain). The significance of such effects is explored for four different classes of algorithms: low-rank compression, quasi-Monte Carlo integration, ...