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I've seen this concept explained as Solomonoff induction, a formalization of Occam's razor. Given some set of Turing machines that fit the data, the one with the lowest complexity is likely to be the one that truly models it.


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You can say that an algorithm is asymptotically optimal in such a case. In general, people might also say that an algorithm is optimal in some other sense, like assuming some particular complexity-theoretic conjecture like (S)ETH.


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