Noteworthy Uses:: *[[Noteworthy Uses]]*
Proved By:: [[derivative of the dot product]]
Intuition:: *[[Intuition]]*
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> [!proposition] Proposition. ([[derivative of a quadratic form]])
> The [[derivative]] of the function $f: \rr ^{d} \to \rr$ given by $f(x)=x^{\top} Ax + b^{\top}x + c$ is $D(x^{\top}Ax)+ D(b^{\top}x)+ D(c),$ where $D(x^{\top}Ax)=x^{\top}(A + A^{\top})$, $D(b^{\top}x)=b^{\top}$, and $D(c)=0$.
>
> **Remark.** If $A$ is a [[symmetric matrix]], part of the result simplifies to $D(x^{\top}Ax)=2x^{\top}A$.
> [!proposition] Corollary. (Gradient of a quadratic form)
> The [[gradient|gradient]] of the above [[quadratic form]] is $\nabla(x^{\top}Ax+b^{\top}x+c)=(A+A^{\top})x+b + 0.$
> [!proof]- Proof. ([[derivative of a quadratic form]])
> The computation is straightforward but a little messy. Using linearity of the [[derivative]] we will compute $D(x^{\top}Ax)$, $D(b^{\top}x)$, and $D(c)$ one at a time and sum the result. Recalling the relationship between the [[dot product]] and [[matrix transpose]] and specifically the [[derivative of the dot product]], we have $\begin{align}D(x^{\top}Ax) = & D(x \cdot Ax) \\= & x^{\top}D(Ax) + (Ax)^{\top} D(Ix) \\
= & x^{\top}A + x^{\top}{ A^{\top}}I \\
= & x^{\top}(A+A^{\top});
\end{align}$
this is the claimed form of $D(x^{\top}Ax)$.
\
Next consider $D(b^{\top}x)$. This is just a constant [[matrix]] times $x$ so the answer is $b^{\top}$.
\
Finally, it is obvious that $D(c)=0$.
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#### References
> [!backlink]
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> ```
> [!frontlink]
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