Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
Browsing by Subject High Dimensional and Sparse Data
Showing results 1 to 1 of 1
| Issue Date | Title | Author(s) |
|---|---|---|
| 2019 | An Instance-Frequency-Weighted Regularization Scheme for Non-Negative Latent Factor Analysis on High-Dimensional and Sparse Data | Luo, X; Wang, Z; Shang, M |