A fast proximal method for convolutional sparse coding

@article{Chalasani2013AFP,
  title={A fast proximal method for convolutional sparse coding},
  author={Rakesh Chalasani and Jos{\'e} Carlos Pr{\'i}ncipe and Naveen Ramakrishnan},
  journal={The 2013 International Joint Conference on Neural Networks (IJCNN)},
  year={2013},
  pages={1-5}
}
Sparse coding, an unsupervised feature learning technique, is often used as a basic building block to construct deep networks. Convolutional sparse coding is proposed in the literature to overcome the scalability issues of sparse coding techniques to large images. In this paper we propose an efficient algorithm, based on the fast iterative shrinkage thresholding algorithm (FISTA), for learning sparse convolutional features. Through numerical experiments, we show that the proposed convolutional… CONTINUE READING

Citations

Publications citing this paper.
SHOWING 1-10 OF 36 CITATIONS

References

Publications referenced by this paper.
SHOWING 1-10 OF 22 REFERENCES

Learning Deep Architectures for AI

  • Yoshua Bengio
  • Found. Trends Mach. Learn., vol. 2, no. 1, pp. 1…
  • 2009
1 Excerpt

Similar Papers

Loading similar papers…