Riesz representation is a theorem stating that in a Hilbert space $\mathcal{F}$, every continuous linear functional $L:\mathcal{F}\rightarrow\mathbb{R}$ can be written as $Lf=\left\langle f,g\right\rangle _{\mathcal{F}}$ for a unique $g\in\mathcal{F}$.

Proof. Assume that the linear functional $L$ is continuous. For the edge case where $Lf=0$ for all $f$, this is trivial because $Lf=\left\langle f,0\right\rangle$, so $g=0$. If not, we know that the null space of $L$ i.e., $N=\{f\mid Lf=0\}=L^{-1}\left(\{0\}\right)$ is closed because a continuous operator maps a closed set to a closed set i.e., $\{0\}$. Since $N$ is closed, the orthogonal complement $N^{\perp}$ (subspace of elements orthogonal to $N$) contains elements other than $0$ element. Consider $h\in N^{\perp}$ such that $\|h\|_{\mathcal{F}}=1$. Consider $u_{f}=\left(Lf\right)h-\left(Lh\right)f\in N$ (i.e., $Lu_{f}=0$). Since $h$ and $u_{f}$ are orthogonal by construction, we have $\begin{eqnarray*} 0 & = & \left\langle u_{f},h\right\rangle _{\mathcal{F}}\\ & = & \left\langle \left(Lf\right)h-\left(Lh\right)f,h\right\rangle _{\mathcal{F}}\\ & = & \left(Lf\right)\|h\|^{2}-\left(Lh\right)\left\langle f,h\right\rangle \\ & = & Lf-\left\langle f,(Lh)h\right\rangle _{\mathcal{F}}\\ \Rightarrow Lf & = & \left\langle f,(Lh)h\right\rangle _{\mathcal{F}}. \end{eqnarray*}$ Hence, $g=\left(Lh\right)h$ for some $h\in N^{\perp}$.

The element $g$ is unique. If there were $g_{1}$ and $g_{2}$, then $0=|Lf-Lf|=|\left\langle f,g_{1}-g_{2}\right\rangle |\leq\|f\|\|g_{1}-g_{2}\|$ by Cauchy-Schwarz inequality. This implies $\|g_{1}-g_{2}\|=0$. Hence $g_{1}=g_{2}$. Riesz representation is useful in establishing the existence of a mean embedding in RKHS of a probability distribution.

Reference: Dino Sejdinovic's teaching slides