Gespeichert in:
| 1. Verfasser: | |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2406.01739 |
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Inhaltsangabe:
- We introduce a decomposition method for the distributed calculation of exact Euclidean Minimum Spanning Trees in high dimensions (where sub-quadratic algorithms are not effective), or more generalized geometric-minimum spanning trees of complete graphs, where for each vertex $v\in V$ in the graph $G=(V,E)$ is represented by a vector in $\vec{v}\in \mathbb{R}^n$, and each for any edge, the the weight of the edge in the graph is given by a symmetric binary `distance' function between the representative vectors $w(\{x,y\}) = d(\vec{x},\vec{y})$. This is motivated by the task of clustering high dimensional embeddings produced by neural networks, where low-dimensional algorithms are ineffective; such geometric-minimum spanning trees find applications as a subroutine in the construction of single linkage dendrograms, as the two structures can be converted between each other efficiently.