  Dual gradient descent combined with early stopping represents an efficient
alternative to the Tikhonov variational approach when the regularizer is
strongly convex. However, for many relevant applications, it is crucial to deal
with regularizers which are only convex. In this setting, the dual problem is
non smooth, and dual gradient descent cannot be used. In this paper, we study
the regularization properties of a subgradient dual flow, and we show that the
proposed procedure achieves the same recovery accuracy as penalization methods,
while being more efficient from the computational perspective.
