Online Robust Dictionary Learning
| Autor: | Jiaya Jia, Cewu Lu, Jiaping Shi |
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| Rok vydání: | 2013 |
| Předmět: |
Training set
K-SVD Group method of data handling Active learning (machine learning) business.industry Computer science Robust statistics Online machine learning Usability Semi-supervised learning Machine learning computer.software_genre Outlier Curve fitting Artificial intelligence business computer Sparse matrix |
| Zdroj: | CVPR |
| DOI: | 10.1109/cvpr.2013.60 |
| Popis: | Online dictionary learning is particularly useful for processing large-scale and dynamic data in computer vision. It, however, faces the major difficulty to incorporate robust functions, rather than the square data fitting term, to handle outliers in training data. In this paper, we propose a new online framework enabling the use of l1 sparse data fitting term in robust dictionary learning, notably enhancing the usability and practicality of this important technique. Extensive experiments have been carried out to validate our new framework. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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