Differentiable Kernels in Generalized Matrix Learning Vector Quantization

Marika Kästner, David Nebel, Martin Riedel, Michael Biehl, Thomas Villmann. Differentiable Kernels in Generalized Matrix Learning Vector Quantization. In 11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA, December 12-15, 2012. Volume 1. pages 132-137, IEEE, 2012. [doi]

@inproceedings{KastnerNRBV12,
  title = {Differentiable Kernels in Generalized Matrix Learning Vector Quantization},
  author = {Marika Kästner and David Nebel and Martin Riedel and Michael Biehl and Thomas Villmann},
  year = {2012},
  doi = {10.1109/ICMLA.2012.231},
  url = {http://dx.doi.org/10.1109/ICMLA.2012.231},
  researchr = {https://researchr.org/publication/KastnerNRBV12},
  cites = {0},
  citedby = {0},
  pages = {132-137},
  booktitle = {11th International Conference on Machine Learning and Applications, ICMLA, Boca Raton, FL, USA, December 12-15, 2012. Volume 1},
  publisher = {IEEE},
  isbn = {978-1-4673-4651-1},
}