Robust Dictionary Learning by Error Source Decomposition

@article{Chen2013RobustDL,
  title={Robust Dictionary Learning by Error Source Decomposition},
  author={Zhuoyuan Chen and Ying Wu},
  journal={2013 IEEE International Conference on Computer Vision},
  year={2013},
  pages={2216-2223}
}
Sparsity models have recently shown great promise in many vision tasks. Using a learned dictionary in sparsity models can in general outperform predefined bases in clean data. In practice, both training and testing data may be corrupted and contain noises and outliers. Although recent studies attempted to cope with corrupted data and achieved encouraging results in testing phase, how to handle corruption in training phase still remains a very difficult problem. In contrast to most existing… CONTINUE READING
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