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Jul 1, 2021 at 12:02 review Close votes
Jul 12, 2021 at 0:05
Jun 29, 2021 at 14:10 history edited Daniele Tampieri CC BY-SA 4.0
(Very) Minor Math Jaxing (used $\|\cdot\|$ instead of $||\cdot||$)
Jun 29, 2021 at 14:00 comment added user44143 If all you want is a bound from above, then let $p$ be the minimum of $X\cup Y$ (i.e. the first coordinate of $p$ is the minimum of all the first coordinates), and let $q$ be the maximum, and the distance between $p$ and $q$ provides an upper bound.
Jun 29, 2021 at 13:13 answer added Iosif Pinelis timeline score: 4
Jun 29, 2021 at 13:04 comment added Flore @MattF. So the most important and interesting is to find a known efficient method to find the nearest neighbor for all points in huge sets then I can work on the bound for the distance
Jun 29, 2021 at 13:01 comment added Flore @MattF. As you know, the distance above is used as a metric to compare the similarity between two sets in neural networks. Unfortunately, I can't compute it exactly because of the amount of points since it needs to to search for the closest neighbor in Y for each point in X and to do the same again for each point in Y. Consequently, I am looking in literature for efficient methods to find the nearest neighbor in order to use them and to bound the distances above.
Jun 29, 2021 at 12:50 history edited user44143 CC BY-SA 4.0
deleted 6 characters in body
Jun 29, 2021 at 12:49 comment added Flore @MattF. Thanks for your help and the edit. I wrote to bound in the original question because it is hard to compute the distance exactly and an algorithm should be used to approximate or bound the distance. Hope it is clear?
Jun 29, 2021 at 12:42 history edited user44143 CC BY-SA 4.0
simplified and retagged
Jun 29, 2021 at 12:31 review First posts
Jun 29, 2021 at 14:10
Jun 29, 2021 at 12:29 history asked Flore CC BY-SA 4.0