Name
Abstract | ||
|---|---|---|
•A novel randomized hierarchical alternating least squares algorithm for NMF.•The randomized algorithm scales up to big data.•The algorithm outperforms previous compressed NMF algorithms in speed and accuracy.•Both synthetic and real-world data are used for evaluation.•A Python implementation is provided on GitHub. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.patrec.2018.01.007 | Pattern Recognition Letters |
Keywords | DocType | Volume |
NMF,Randomized algorithm,Dimension reduction | Journal | 104 |
ISSN | Citations | PageRank |
0167-8655 | 3 | 0.38 |
References | Authors | |
31 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| n benjamin erichson | 1 | 26 | 5.69 |
| Ariana Mendible | 2 | 3 | 0.38 |
| Sophie Wihlborn | 3 | 3 | 0.38 |
| J. Nathan Kutz | 4 | 225 | 47.13 |