Moreau envelope

The Moreau envelope of a proper lower semi-continuous convex function ${\displaystyle f}$ from a Hilbert space ${\displaystyle {\mathcal {X}}}$ to ${\displaystyle (-\infty ,+\infty ]}$ is defined as[2]

${\displaystyle M_{\lambda f}(v)=\inf _{x\in {\mathcal {X}}}\left(f(x)+{\frac {1}{2\lambda }}\|x-v\|_{2}^{2}\right).}$

Given a parameter ${\displaystyle \lambda \in \mathbb {R} }$, the Moreau envelope of ${\displaystyle \lambda f}$ is also called as the Moreau envelope of ${\displaystyle f}$ with parameter ${\displaystyle \lambda }$.[2]

• The Moreau envelope can also be seen as the infimal convolution between ${\displaystyle f}$ and ${\displaystyle (1/2)\|\cdot \|_{2}^{2}}$.
• The proximal operator of a function is related to the gradient of the Moreau envelope by the following identity:

${\displaystyle \nabla M_{\lambda f}(x)={\frac {1}{\lambda }}(x-\mathrm {prox} _{\lambda f}(x))}$. By defining the sequence ${\displaystyle x_{k+1}=\mathrm {prox} _{\lambda f}(x_{k})}$ and using the above identity, we can interpret the proximal operator as a gradient descent algorithm over the Moreau envelope.

• By Hopf-Lax formula, the Moreau envelope is a viscosity solution to a Hamilton-Jacobi equation.[3] Stanley Osher and co-authors used this property and Cole-Hopf transformation to derive an algorithm to compute approximations to the proximal operator of a function.[4]

• Proximal operator
• Proximal gradient method

• "Moreau envelope function", Encyclopedia of Mathematics, EMS Press, 2001 [1994]
• A Hamilton-Jacobi-based Proximal Operator: a YouTube video explaining an algorithm to approximate the proximal operator