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Denote by $y^*$ the shortest program computing the string $y$. In the main textbook and various papers of Li & Vitanyi, I have seen the following statements.

The first is well established: the symmetry of information

$K(x,y) = K(y) + K(x|y^*) = K(x) + K(y|x^*)$ (up to additive constants)

I have also seen them drop the $y^*$ and assert that this equality is still true up to additive constant precision (say, in the paper "The Similarity Metric" (bottom of page 8, first column)). On the other hand, I have only been able to prove that

$K(x|y^*) \leq K(x|y) + O(1)$, and

$K(x|y) \leq K(x|y^*) + O(\log(K(y)))$

And it appears that the latter is not true if we replace the logarithm with a constant. For instance, $K(K(x)|x)$ is ostensibly logarithmic in size (since $K$ is uncomputable), but $K(K(x)|x^*)$ is easily seen to be a constant.

My question is, how can they assert that $K(x|y) = K(x,y)-K(y)$ without having $K(x|y^*) = K(x|y)$ up to an additive constant?

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After a while it appears to me that this is either a typo or intentional sloppiness to emphasize the fact that these are approximations in practice. Oh well. –  JeremyKun Dec 21 '12 at 1:41
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