CUR matrix approximation through convex optimization for feature selection
The singular value decomposition (SVD) is commonly used in applications that require a low-rank matrix approximation. However, the singular vectors cannot be interpreted in terms of the original data. For applications requiring this type of interpretation, e.g., selection of important data matrix co...
| الحاوية / القاعدة: | Frontiers in Applied Mathematics and Statistics |
|---|---|
| المؤلفون الرئيسيون: | , |
| التنسيق: | مقال |
| اللغة: | الإنجليزية |
| منشور في: |
Frontiers Media S.A.
2025-08-01
|
| الموضوعات: | |
| الوصول للمادة أونلاين: | https://www.frontiersin.org/articles/10.3389/fams.2025.1632218/full |