Sparse low-rank matrix approximation for data compression

• المؤلفون الرئيسيون: Hou, Junhui, Chau, Lap-Pui, Magnenat-Thalmann, Nadia, He, Ying
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2018
• الموضوعات: Optimization; DRNTU::Engineering::Computer science and engineering; Data Compression; DRNTU::Engineering::Electrical and electronic engineering
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/89401; http://hdl.handle.net/10220/46229
• المؤسسة: Nanyang Technological University

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...