ℓ 1 penalty methods such as Lasso, being convex, can be solved by optimization and give guaranteed optimal solutions.
ℓ 0 penalty methods, like stepwise feature selection, give approximate solutions but produce models that are much sparser than the models given by ℓ 1 methods, which is quite crucial in WSD (Florian and Yarowsky, 2002).