Unsupervised feature learning with C-SVDDNet

@article{Wang2016UnsupervisedFL,
  title={Unsupervised feature learning with C-SVDDNet},
  author={Dong Wang and Xiaoyang Tan},
  journal={Pattern Recognition},
  year={2016},
  volume={60},
  pages={473-485}
}
In this paper we present a novel unsupervised feature learning network named C-SVDDNet, a singlelayer K-means-based network towards compact and robust feature representation. Our contributions are three folds: (1) we introduce C-SVDD encoding, a generalization of the K-means local encoding that adapts to the distribution information and improves the robustness against outliers; (2) we propose a method that effectively embeds the spatial information of 2D data into the final representation based… CONTINUE READING
Highly Cited
This paper has 24 citations. REVIEW CITATIONS
Recent Discussions
This paper has been referenced on Twitter 3 times over the past 90 days. VIEW TWEETS
12 Citations
59 References
Similar Papers

Citations

Publications citing this paper.
Showing 1-10 of 12 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 59 references

An analysis of single-layer networks in unsupervised feature learning

  • A. Coates, H. Lee, A. Y. Ng
  • Ann Arbor 1001
  • 2010
Highly Influential
10 Excerpts

Deep learning

  • Y. LeCun, Y. Bengio, G. Hinton
  • Nature 521 (7553)
  • 2015
1 Excerpt

Similar Papers

Loading similar papers…