Similarity Problems in High Dimensions
Abstract
The main contribution of this dissertation is the introduction of new or improved approximation algorithms and data structures for several similarity search problems. We examine the furthest neighbor query, the annulus query, distance sensitive membership, nearest neighbor preserving embeddings and set similarity queries in the large-scale, high-dimensional setting.
- Publication:
-
arXiv e-prints
- Pub Date:
- June 2019
- DOI:
- 10.48550/arXiv.1906.04842
- arXiv:
- arXiv:1906.04842
- Bibcode:
- 2019arXiv190604842V
- Keywords:
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- Computer Science - Data Structures and Algorithms
- E-Print:
- Dissertation, Univ Copenhagen (2017)