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For instance, it is believed that for any $\epsilon>0$ there is an algorithm for matrix multiplication that runs in $O(n^{2+\epsilon})$, but possibly no algorithm that runs in $O(n^2)$. How is this possible? Couldn't we create a meta-algorithm that runs in $O(n^2)$ time by using a better and better algorithm to solve problems of bigger size?

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    $\begingroup$ There seem to be two questions here: (1) how can you have an algorithm for a problem with running time $n^{c+\epsilon}$ and (2) how can matrix multiplication admit such a method. Which one is it ? $\endgroup$ Mar 26 '12 at 16:04
  • $\begingroup$ I'm trying to ask (1). I've edited the question. Is it clearer now? $\endgroup$
    – Jules
    Mar 26 '12 at 16:09
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    $\begingroup$ There is a comparison-based sorting algorithm with complexity $O(n^{1+\epsilon})$ for all $\epsilon > 0$, but there is no such algorithm with complexity $O(n)$. $\endgroup$ Mar 26 '12 at 16:14
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    $\begingroup$ Yes, see e.g. blog.computationalcomplexity.org/2004/04/… $\endgroup$ Mar 26 '12 at 17:23
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    $\begingroup$ Usually that notation means that the constant hidden by the big-Oh notation depends on ε (and diverges as ε goes to zero). Moreover, either the dependence is too complicated to solve for the best value of ε, or the author was too lazy to try. $\endgroup$
    – Jeffε
    Mar 26 '12 at 18:53
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In this case, it's another way of saying that the algorithm runs in time $O(n^{2+o(1)})$; for example $O(n^2 \log^6 n)$ or $O(n^2 2^{\sqrt{\log n}})$ would both qualify.

Sometimes there are parameters other than the running time involved in an algorithm, for example quality of an approximation, that depend on $\epsilon$. In such cases, an algorithm may be designed to accept a parameter $\epsilon$ as a part of the input and adjust its performance accordingly.

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    $\begingroup$ This is not necessarily equivalent. Having a single algorithm in time $n^{2+o(1)}$ is a stronger condition than having infinitely many separate algorithms (which may not be computable) with running time $n^{2+\epsilon}$. $\endgroup$ Mar 26 '12 at 19:23

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