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Often we use PQ to estimate the distance from a full precision vector to a bunch of compressed points.
However, we can also try to compute the distance between all pairs of points in two compressed datasets (even possibly with distinct FastPQ instances).
This is relevant, for example, when inserting a batch of points into the data structure, when we quickly want to compute all the relevant close cluster centers.
Currently we compute this using full precision distance computations.
Edit: Maybe #13 is more relevant for speeding up building the index. However, supporting estimating distances between compressed datasets is still interesting and worthwhile.
The text was updated successfully, but these errors were encountered:
Often we use PQ to estimate the distance from a full precision vector to a bunch of compressed points.
However, we can also try to compute the distance between all pairs of points in two compressed datasets (even possibly with distinct FastPQ instances).
This is relevant, for example, when inserting a batch of points into the data structure, when we quickly want to compute all the relevant close cluster centers.
Currently we compute this using full precision distance computations.
Edit: Maybe #13 is more relevant for speeding up building the index. However, supporting estimating distances between compressed datasets is still interesting and worthwhile.
The text was updated successfully, but these errors were encountered: