.png){kind=icon}
返回
A Reliable Order-Statistics-Based Approximate Nearest Neighbor Search Algorithm
.png){kind=icon}
OA
AI
DOI：10.1109/TIP.2016.2624141.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We propose a new algorithm for fast approximate nearest neighbor search based on the properties of ordered vectors. Data vectors are classified based on the index and sign of their largest components, thereby partitioning the space in a number of cones centered in the origin. The query is itself classified, and the search starts from the selected cone and proceeds to neighboring ones. Overall, the proposed algorithm corresponds to locality sensitive hashing in the space of directions, with hashing based on the order of components. Thanks to the statistical features emerging through ordering, it deals very well with the challenging case of unstructured data, and is a valuable building block for more complex techniques dealing with structured data. Experiments on both simulated and real-world data prove the proposed algorithm to provide a state-of-the-art performance.
Keyword:
Approximate nearest neighbor search
locality sensitive hashing
vector quantization
order statistics
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
13.7
论文数:
1.0W
被引数:
8.4W
机构
引用论文
Northward oceanic heat transport in the main branch of the Norwegian Atlantic Current over the late Holocene.png)
The Holocene
The HoloceneIF0
PREAI
分享收藏
查看更多内容