Loading…
Low-Rank and Sparse Modeling for Visual Analysis
This book provides a view of low-rank and sparse computing, especially approximation, recovery, representation, scaling, coding, embedding, and learning among unconstrained visual data. Included in the book are chapters covering multiple emerging topics in this new field. The text links multiple pop...
| Call Number: | Libro Electrónico |
|---|---|
| Corporate Author: | |
| Other Authors: | |
| Format: | Electronic eBook |
| Language: | Inglés |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2014.
|
| Edition: | 1st ed. 2014. |
| Subjects: | |
| Online Access: | Texto Completo |
Table of Contents:
- Nonlinearly Structured Low-Rank Approximation
- Latent Low-Rank Representation
- Scalable Low-Rank Representation
- Low-Rank and Sparse Dictionary Learning
- Low-Rank Transfer Learning
- Sparse Manifold Subspace Learning
- Low Rank Tensor Manifold Learning
- Low-Rank and Sparse Multi-Task Learning
- Low-Rank Outlier Detection
- Low-Rank Online Metric Learning.