Reliable, efficient and light distance computation on high-dimensional vectors
The great advances in deep learning enable human beings to extract the semantic information in ubiquitous unstructured data into high-dimensional vectors, leading to an urgent priority of managing vector data. Nearest neighbor (NN) query is a pivotal question in vector data management. Unfortunately...
Saved in:
Main Author: | Gao, Jianyang |
---|---|
Other Authors: | Long Cheng |
Format: | Thesis-Doctor of Philosophy |
Language: | English |
Published: |
Nanyang Technological University
2025
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/182813 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
HDIdx: High-dimensional indexing for efficient approximate nearest neighbor search
by: WAN, Ji, et al.
Published: (2016) -
Scalable image retrieval by sparse product quantization
by: NING, Qingqun, et al.
Published: (2017) -
Approximate k-NN graph construction: A generic online approach
by: ZHAO, Wan-Lei, et al.
Published: (2022) -
BORDER: Efficient computation of boundary points
by: Xia, C., et al.
Published: (2013) -
THE DISTANCE-AGGREGATION QUERY IN SUB-LINEAR TIME
by: LEI YIFAN
Published: (2021)