Projection Theorem for closed convex set

convex-analysisoptimizationprojection

Consider the following statement:

Let $C \subset \mathbb{R}^{n}$ be a closed convex set. For $x \in \mathbb{R}^{n}$ the projection of $x$ on $C$, denoted by $\text{Proj}_{C}(x)$, is defined as follows

$$
\text{Proj}_{C}(x) = \text{argmin}_{y \in C} ||x-y||_{2}^{2}.
$$

Then it can be shown that $\text{Proj}_{C}(x)$ is unique for all $x \in \mathbb{R}^{n}$. Why the set $C$ must be closed or convex for the uniqueness?

Best Answer

If it's not closed, the projection might not exist. Consider e.g. $C = (0,1) \subseteq \mathbb{R}$ and $x = 2$.

If it's not convex the projection might not be unique. For this case consider e.g. $C = \{0\} \cup \{2\} \subseteq \mathbb{R}$ and $x = 1$. All elements in $C$ minimize the distance to $x$.

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