# How to Derive the Proximal Operator of the Euclidean Norm?

I'm trying to derive the proximal operator of the $L_2$ norm for myself. Here is my effort: let

$$g(x)=\gamma ||x||_2.$$

The prox-operator of $g$ at the point $x$ is defined as follows: $$\text{prox}_g(x)={\arg\,\min}_u \, g(u) + \frac{1}{2} \|u-x\|_2^2 .$$

In order to minimize it, we can take the derivatives of it :

$$0 \in \gamma \partial||u||_2 + u-x$$

then I can rewrite the above equation as follows: $u \in x- \gamma \partial |||u||_2$. From there, I do not know how to further simplify it. I was wondering whether can someone help me to understand it better ? I know that, people have simplified it and derived a closed formula solution for it, but I'm not sure how they did it.

• Use the Moreau decomposition: $\forall \lambda > 0$, $$\text{prox}_{\lambda g}(x) \equiv x - \lambda\text{prox}_{g^*/\lambda}(x/\lambda),$$

and note that

• $g^*$ (the convex conjugate of $g$) is the indicator function of the $\ell_2$ unit-ball (because the $\ell_2$ norm is self-dual), i.e $$g^*(x) \equiv i_{\|x\|_2 \le \gamma} = \begin{cases}0, &\mbox{ if } \|x\|_2 \le \gamma,\\+\infty, &\mbox{ otherwise.}\end{cases}$$

• Finally, note that if $C$ is a closed convex set, then $\text{prox}_{i_C}(x) \equiv \text{proj}_C(x)$.

$$\operatorname{Prox}_{\lambda \left\| \cdot \right\|_{2}} \left( v \right) = v - \operatorname{Proj}_{ \mathcal{B}_{ \left\| \cdot \right\|_{2} } } \left( \frac{v}{\lambda} \right) = \begin{cases} v - \lambda \frac{ \frac{v}{\lambda} }{ \left\| \frac{v}{\lambda} \right\|_{2} } & \text{ if } \left\| \frac{v}{\lambda} \right\|_{2} > 1 \\ v - \lambda \frac{v}{\lambda} & \text{ if } \left\| \frac{v}{\lambda} \right\|_{2} \leq 1 \end{cases} = \left(1 - \frac{\lambda}{ \left\| v \right\|_{2} } \right)_{+} v$$
Where $\left( x \right)_{+} = \max \left\{ 0, x \right\}$.