Robust Latent Feature Learning for Incomplete Big Data [E-Book] / by Di Wu.
Incomplete big data are frequently encountered in many industrial applications, such as recommender systems, the Internet of Things, intelligent transportation, cloud computing, and so on. It is of great significance to analyze them for mining rich and valuable knowledge and patterns. Latent feature...
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Full text |
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Personal Name(s): | Wu, Di, author |
Edition: |
1st edition 2023. |
Imprint: |
Singapore :
Springer,
2023
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Physical Description: |
XIII, 112 pages 1 illustration (online resource) |
Note: |
englisch |
ISBN: |
9789811981401 |
DOI: |
10.1007/978-981-19-8140-1 |
Series Title: |
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SpringerBriefs in Computer Science
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Subject (LOC): |
- Chapter 1. Introduction
- Chapter 2. Basis of Latent Feature Learning
- Chapter 3. Robust Latent Feature Learning based on Smooth L1-norm
- Chapter 4. Improving robustness of Latent Feature Learning Using L1-norm
- Chapter 5. Improve robustness of latent feature learning using double-space
- Chapter 6. Data-characteristic-aware latent feature learning
- Chapter 7. Posterior-neighborhood-regularized Latent Feature Learning
- Chapter 8. Generalized deep latent feature learning
- Chapter 9. Conclusion and Outlook. .