Forward subgradient step
= Forward subgradient step
{title2=$F_{ au f}$}
For a <convex function> and $\tau>0$, the forward step is the set-valued explicit update $F_{\tau f}(x)=\{x-\tau p:p\in\partial f(x)\}$. It reduces to the usual gradient step when differentiable. In contrast, a backward step uses a <subgradient> at the new point and is the <proximal operator> for a proper closed convex function.