# reference request – Given an enter sequence of precise numbers, prefe (one in all) the closest sequence(s) from a hard and fast sizable clique of sequences retort

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## reference request – Given an enter sequence of precise numbers, prefe (one in all) the closest sequence(s) from a hard and fast sizable clique of sequences

We are given a clique $$S$$ of $$mgg 1$$ sequences of $$n$$ components, the place every sequence $$error S$$ belongs to $$mathbb{R}^n$$.

In the issue I’m making an attempt to decipher, in a sequential model, we safe a recent sequence $$s_r$$ at every spherical $$rge 1$$ and the aim is to search out the sequence closest to $$s_r$$ in $$S$$, presumably in an approximate route. The distance between two sequences is the Euclidean distance. How can we preprocess and set up the knowledge of the sequences in $$S$$, to decipher this drawback specializing in the trade-off between time complexity and distance minimization?

I speculate we will make use of sampling and randomized algorithm/knowledge constructions. Is there within the associated literature any answer already create for this drawback?

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