@inproceedings{bibcite_419,
  author = {Franciso Javier Pulgar Rubio and Francisco Charte Ojeda and Antonio Jes{\'u}s Rivera Rivas and Maria Jos{\'e} del Jesus D{\'\i}az},
  title = {A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders},
  abstract = {The problem of high dimensionality is a challenge when facing machine learning tasks. A high dimensional space has a negative effect on the predictive performance of many methods, specifically, classification algorithms. There are different proposals that arise to mitigate the effects of this phenomenon. In this sense, models based on deep learning have emerged.},
  year = {2018},
  pages = {439-447},
  month = {11},
  address = {Madrid (Spain)},
  isbn = {978-3-030-03493-1},
  doi = {10.1007/978-3-030-03493-1_46},
  note = {TIN2015-68854-R; FPU16/00324},
}