Name
Title | ||
|---|---|---|
A Sub-Linear Time Algorithm For Approximating K-Nearest-Neighbor With Full Quality Guarantee |
Abstract | ||
|---|---|---|
In this paper we propose an algorithm for the approximate k-Nearest-Neighbors problem. According to the existing researches, there are two kinds of approximation criteria. One is the distance criterion, and the other is the recall criterion. All former algorithms suffer the problem that there are no theoretical guarantees for the two approximation criteria. The algorithm proposed in this paper unifies the two kinds of approximation criteria, and has full theoretical guarantees. Furthermore, the query time of the algorithm is sub-linear. As far as we know, it is the first algorithm that achieves both sub-linear query time and full theoretical approximation guarantee. (c) 2020 Published by Elsevier B.V. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.tcs.2020.12.039 | THEORETICAL COMPUTER SCIENCE |
Keywords | DocType | Volume |
Computation geometry, Approximate k-nearest-neighbors | Journal | 857 |
ISSN | Citations | PageRank |
0304-3975 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Heng-Zhao Ma | 1 | 1 | 1.71 |
| Jianzhong Li | 2 | 63 | 24.23 |