Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data

Ioannis L. Dallas, Aristidis G. Vrahatis, Sotiris K. Tasoulis, Vassilis P. Plagianakos. Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data. In Davide Chicco, Angelo M. Facchiano, Erica Tavazzi, Enrico Longato, Martina Vettoretti, Anna Bernasconi 0002, Simone Avesani, Paolo Cazzaniga, editors, Computational Intelligence Methods for Bioinformatics and Biostatistics - 17th International Meeting, CIBB 2021, Virtual Event, November 15-17, 2021, Revised Selected Papers. Volume 13483 of Lecture Notes in Computer Science, pages 227-241, Springer, 2021. [doi]

@inproceedings{DallasVTP21,
  title = {Recent Dimensionality Reduction Techniques for High-Dimensional COVID-19 Data},
  author = {Ioannis L. Dallas and Aristidis G. Vrahatis and Sotiris K. Tasoulis and Vassilis P. Plagianakos},
  year = {2021},
  doi = {10.1007/978-3-031-20837-9_18},
  url = {https://doi.org/10.1007/978-3-031-20837-9_18},
  researchr = {https://researchr.org/publication/DallasVTP21},
  cites = {0},
  citedby = {0},
  pages = {227-241},
  booktitle = {Computational Intelligence Methods for Bioinformatics and Biostatistics - 17th International Meeting, CIBB 2021, Virtual Event, November 15-17, 2021, Revised Selected Papers},
  editor = {Davide Chicco and Angelo M. Facchiano and Erica Tavazzi and Enrico Longato and Martina Vettoretti and Anna Bernasconi 0002 and Simone Avesani and Paolo Cazzaniga},
  volume = {13483},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-031-20837-9},
}