Corpus ID: 57189419

Approximate Nearest Neighbors in the Space of Persistence Diagrams

@article{Fasy2018ApproximateNN,
  title={Approximate Nearest Neighbors in the Space of Persistence Diagrams},
  author={Brittany Terese Fasy and Xiaozhou He and Zhihui Liu and Samuel Micka and David L. Millman and Binhai Zhu},
  journal={ArXiv},
  year={2018},
  volume={abs/1812.11257}
}
Persistence diagrams are important tools in the field of topological data analysis that describe the presence and magnitude of features in a filtered topological space. However, current approaches for comparing a persistence diagram to a set of other persistence diagrams is linear in the number of diagrams or do not offer performance guarantees. In this paper, we apply concepts from locality-sensitive hashing to support approximate nearest neighbor search in the space of persistence diagrams… Expand
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