[highd]

Another pro tip - absolute error magnitude is the convex hull of non-zero entry count for vectors (l_0 norm in some circles). So in the convex minimization context (and for most other smooth loss terms in general) you end up with solutions with more zero entries and few possibly large non-zero entries.