Proving the function is a kernel

kernel trick

I have an exercise in my book, which I'm not sure if I have answered correctly. Here's the exercise:

For the function $K: \mathbb{R}^2\times \mathbb{R}^2\to \mathbb{R}$ such that $$K(x,t)=x^TDt$$, where $$D=\begin{pmatrix} -1 && 2 \\ 2 &&4 \end{pmatrix}$$

Determine whether the function is a valid kernel (i.e., the kernel can be written as an inner product in some feature space) and when the answer is positive derive an associated feature map representation.

In this question, it is said that we have to check that the funciton $k(x,t)$ is symmetric and also whether it is positive definite. So, the function is symmetric. We need to check if it's PSD.

We check it by inspecting for an "inner-product" representation. I would like to find a $\phi(a)$, such that $k(x,t)=\phi(x)^T\phi(t)$. Well, $$\phi(a)=(ia_1,\sqrt{2}a_1,\sqrt{2}a_2,2a_2)^T$$

Hence, $K$ is a valid kernel.

EDIT

There is no such function, because the indices in $K(x,t)=x^TDt=-x_1t_1+2x_2t_1+2x_1t_2+4x_2t_2$ are "mixed", i.e., $x_1$ is multiplied by $t_2$, so there is no such function $\phi(a)$.

Hence $K$ is not a valid kernel.

Is this correct?

Best Answer

Checking $K((1,0), (1,0)) < 0$ rules out that the possibility that it can be a kernel.

Checking whether $x^TDx$ is a valid kernel is equivalent to checking if $D$ is positive semidefinite.

Mixing indices can occur in matrix in the expression of $K(x,t)$, for example if $D=\begin{bmatrix} 4 & 2 \\ 2 & 4\end{bmatrix}$, then $K$ is a valid kernel since it is positive semidefnite.

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