Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Nearest Neighbor Search for Hyperbolic Embeddings   Embedding into hyperbolic space is emerging as an effective representation
technique for datasets that exhibit hierarchical structure. This development
motivates the need for algorithms that are able to effectively extract
knowledge and insights from datapoints embedded in negatively curved spaces. We
focus on the problem of nearest neighbor search, a fundamental problem in data
analysis. We present efficient algorithmic solutions that build upon
established methods for nearest neighbor search in Euclidean space, allowing
for easy adoption and integration with existing systems. We prove theoretical
guarantees for our techniques and our experiments demonstrate the effectiveness
of our approach on real datasets over competing algorithms.

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The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
25
The categories of this paper are: patt-sol
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph
4
The categories of this paper are: cond-mat