Sparse low-rank matrix approximation for data compression

Sparse low-rank matrix approximation for data compression

Low-rank matrix approximation (LRMA) is a powerful technique for signal processing and pattern analysis. However, its potential for data compression has not yet been fully investigated. In this paper, we propose sparse LRMA (SLRMA), an effective computational tool for data compression. SLRMA extends...

Full description

Saved in:
Bibliographic Details
Main Authors: Hou, Junhui, Chau, Lap-Pui, Magnenat-Thalmann, Nadia, He, Ying
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2018
Subjects:
Optimization
DRNTU::Engineering::Computer science and engineering
Data Compression
DRNTU::Engineering::Electrical and electronic engineering
Online Access:https://hdl.handle.net/10356/89401
http://hdl.handle.net/10220/46229
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/89401
http://hdl.handle.net/10220/46229

Similar Items