We use convex geometry to show that the behaviour of training methods such as MERT (Och, 2003;Macherey et al., 2008), MIRA (Crammer et al., 2006), PRO (Hopkins and May, 2011), and others converge with a high feature dimension.
we analyse how robustness decreases in linear models as feature dimension increases.