I am working with a box-embedding-based method in machine learning, and for a particular problem, I have two objects that are represented as two $n$-cubes in $n$-dimension ($n$ might be $16, 32, 64, ...,$ so the method should be general for an arbitrary $n$). Now I need to compute some heuristics distance between these cubes. Currently, I have the minimum and maximum values on each dimension of each cube. I think that one possible start for me is to calculate the distance between the centers of the cubes. However, I am not sure what the way to proceed is, as I found no reference for calculating the centers of the cubes.
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Think on the case $n=2$. – jjagmath Jun 19 '20 at 11:43
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I know how to find the center with $n = 2$ by finding the average on both direction, I'm just not sure if that can be generalized to $n>2$ since I cannot find any source confirming that. Can it be generalized to $n>2$? – Hữu Nghĩa Nguyễn Hồ Jun 20 '20 at 04:59
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Yes, it can be generalized – jjagmath Jun 20 '20 at 11:21