Bilinear Discriminant Component Analysis

@article{Dyrholm2007BilinearDC,
  title={Bilinear Discriminant Component Analysis},
  author={Mads Dyrholm and Christoforos Christoforou and Lucas C. Parra},
  journal={Journal of Machine Learning Research},
  year={2007},
  volume={8},
  pages={1097-1111}
}
Factor analysis and discriminant analysis are often used as complementary approaches to identify linear components in two dimensional data arrays. For three dimensional arrays, which may organize data in dimensions such as space, time, and trials, the opportunity arises to combine these two approaches. A new method, Bilinear Discriminant Component Analysis (BDCA), is derived and demonstrated in the context of functional brain imaging data for which it seems ideally suited. The work suggests to… CONTINUE READING
Highly Cited
This paper has 80 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 42 extracted citations

81 Citations

051015'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 81 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 33 references

Neural Networks for Pattern Recognition

  • C. M. Bishop
  • 1996
Highly Influential
5 Excerpts

Characterization of a family of algorithms for generalized discriminant analysis on undersampled problems

  • J. Ye
  • Journal of Machine Learning Research,
  • 2005
1 Excerpt

Similar Papers

Loading similar papers…