IK-SVD: Dictionary Learning for Spatial Big Data via Incremental Atom Update

@article{Wang2014IKSVDDL,
  title={IK-SVD: Dictionary Learning for Spatial Big Data via Incremental Atom Update},
  author={Lizhe Wang and Ke Lu and Peng Liu and Rajiv Ranjan and Lajiao Chen},
  journal={Computing in Science & Engineering},
  year={2014},
  volume={16},
  pages={41-52}
}
A large group of dictionary learning algorithms focus on adaptive sparse representation of data. Almost all of them fix the number of atoms in iterations and use unfeasible schemes to update atoms in the dictionary learning process. It's difficult, therefore, for them to train a dictionary from Big Data. A new dictionary learning algorithm is proposed here by extending the classical K-SVD method. In the proposed method, when each new batch of data samples is added to the training process, a… CONTINUE READING

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