Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study
By Jarkko Venna, Samuel Kaski. International Conference on Artificial Neural Networks, 2001
324 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Ecology
View Paper: https://www.semanticscholar.org/paper/b08b968ff444eac2aaf6bd4a451b705c15989c78
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- John Aldo Lee
- Michel Verleysen
- Johan Himberg
- Fabrizio Esposito
- P. Dupont
- Aapo Hyvärinen
- Bernhard Schölkopf
- Kun Zhang
In Computer Vision and Pattern Recognition
- John Aldo Lee
- Michel Verleysen
- Johan Himberg
- P. Dupont
- Aapo Hyvärinen
- Fabrizio Esposito
- Guillaume Bernard
- Emilie Renard
In Ecology
Citations in the corpus
- Validating the independent components of neuroimaging time series via clustering and visualization (2004, methodology): “We also considered visualization based on the Self-Organizing Map (SOM) since it is reported to be more trustworthy than many MDS-like methods (Nikkilä et al., 2002; Venna and Kaski, 2001).”
- Quality assessment of dimensionality reduction: Rank-based criteria (2009, background): “More recently, new criteria for quality assessment have been proposed, with a broader applicability, such as the trustworthiness and continuity (T&C) measures [37], the local continuity metacriterion (LCMC) [6], and the mean relative rank errors (MRREs) [22].”
- Type 1 and 2 mixtures of Kullback-Leibler divergences as cost functions in dimensionality reduction based on similarity preservation (2013, background): “This distinction exists in other (pairs of) quality indices [43].”
- Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum (2003, unknown): “tracking [102, 103, 437, 551, 611, 727, 910, 947, 974, 999, 1237, 1376, 1390, 1431, 2092, 1793, 2041, 196] trading [344, 329, 1251, 1475, 1473, 1474, 1682] traffic [207, 226, 498, 526, 611, 657, 703, 705, 704, 1444, 1627] transputer [994] traveling salesman problem (TSP) [31, 47, 48, 154, 268, 487, ”
- Icasso: software for investigating the reliability of ICA estimates by clustering and visualization (2003, background): “However, for |rij | the same transformation is not guaranteed to give a distance matrix that would exactly originate from Euclidean distances between points in Rk.”