Intrinsic t-Stochastic Neighbor Embedding for Visualization and Outlier Detection - A Remedy Against the Curse of Dimensionality?

Erich Schubert, Michael Gertz. Intrinsic t-Stochastic Neighbor Embedding for Visualization and Outlier Detection - A Remedy Against the Curse of Dimensionality?. In Christian Beecks, Felix Borutta, Peer Kröger, Thomas Seidl 0001, editors, Similarity Search and Applications - 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings. Volume 10609 of Lecture Notes in Computer Science, pages 188-203, Springer, 2017. [doi]

@inproceedings{SchubertG17,
  title = {Intrinsic t-Stochastic Neighbor Embedding for Visualization and Outlier Detection - A Remedy Against the Curse of Dimensionality?},
  author = {Erich Schubert and Michael Gertz},
  year = {2017},
  doi = {10.1007/978-3-319-68474-1_13},
  url = {https://doi.org/10.1007/978-3-319-68474-1_13},
  researchr = {https://researchr.org/publication/SchubertG17},
  cites = {0},
  citedby = {0},
  pages = {188-203},
  booktitle = {Similarity Search and Applications - 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings},
  editor = {Christian Beecks and Felix Borutta and Peer Kröger and Thomas Seidl 0001},
  volume = {10609},
  series = {Lecture Notes in Computer Science},
  publisher = {Springer},
  isbn = {978-3-319-68474-1},
}