Prove that minimum of the matrix norm is achieved at certain parametres

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Given matrix $A\in R^{n\times m}$ prove that minimum of the $||A-xy^T||$, $||B||=tr(B^TB)$, is achieved when $x$ is an eigenvector of $AA^T$, corresponding to its greatest eigenvalue, and $y$ is an eigenvector of $A^TA$, corresponding to its greatest eigenvalue.

Progress I've made so far:

$f(x,y)=||A-xy^T||=tr(A^TA-2A^Txy^T+yx^Txy^T)$,

$\frac{\partial f(x,y)}{\partial x}=0 \Leftrightarrow tr(-2Ay+2xy^Ty)=0 \Leftrightarrow tr(xy^T)=tr(A)$