How to get the derivative of this convex quadratic

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Discussion Overview

The discussion revolves around finding the derivative of a convex quadratic function represented in matrix form. Participants explore the mathematical process involved in differentiating this function, including considerations of matrix properties and the implications for the derivative's form.

Discussion Character

  • Technical explanation, Mathematical reasoning, Debate/contested

Main Points Raised

  • One participant asks for the derivative of the function and inquires about relevant textbooks.
  • Another participant suggests a link to a previous discussion that may provide assistance.
  • One participant proposes that the derivative is simply Qx - b, drawing an analogy to a second degree polynomial.
  • A different participant counters this by stating that due to the non-commutative nature of matrix multiplication, the derivative must be symmetrized, leading to the expression [(Q+Q^T)/2]x - b.
  • This counterpoint includes an illustrative example in two dimensions to clarify the gradient calculation.

Areas of Agreement / Disagreement

There is disagreement regarding the correct form of the derivative. Some participants support the simpler form Qx - b, while others argue for the symmetrized version, indicating that the discussion remains unresolved.

Contextual Notes

The discussion highlights the importance of understanding matrix properties in differentiation, particularly regarding symmetry and commutativity, which may not be fully addressed in the initial claims.

justin_huang
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[itex]\frac{d}{dx}f(x)=\frac{d}{dx}[ \frac{1}{2}x_{}^{T}Qx-b_{}^{T}x][/itex]

how to get this derivative, what is the answer? is there textbook describe it?
 
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This equation is analogous to a second degree polynomial, so I think the derivative is simply Qx - b.
 
Not quite. Because multiplication of matrices is not commutative, taking the derivative you have to "symmetrize" Q- the derivative is [itex][(Q+Q^T)/2]x- b[/itex].

Look at the simple two dimensional situation:
[tex]\frac{1}{2}\begin{bmatrix}x & y \end{bmatrix}\begin{bmatrix}a & b \\ c & d \end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}- \begin{bmatrix}e & f\end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}[/tex]
[tex]= \frac{1}{2}ax^2+ \frac{b+ c}{2}xy+ \frac{1}{2}dy^2- ex- ey[/tex]

The "derivative with respect to x", since x is a vector, is the gradient:
[tex]\begin{bmatrix}ax+ \frac{b+c}{2}y- e & dy+ \frac{b+c}{2}x- f\end{bmatrix}[/tex]
[tex]= \begin{bmatrix}a & \frac{b+c}{2} \\ \frac{b+c}{2} & d\end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}- \begin{bmatrix}e & f\end{bmatrix}[/tex]
 

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