Author:
Rodolphe Priam
Affiliation:
University of Southampton, United Kingdom
Keyword(s):
Data Visualization, Generative Model, Latent Variables, tSNE, Survey.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
High-Dimensional Data and Dimensionality Reduction
;
Information and Scientific Visualization
;
Visual Data Analysis and Knowledge Discovery
Abstract:
In data visualization, a family of methods is dedicated to the symmetric numerical matrices which contain the distances or similarities between high-dimensional data vectors. The method t-Distributed Stochastic Neighbor Embedding and its variants lead to competitive nonlinear embeddings which are able to reveal the natural classes. For comparisons, it is surveyed the recent probabilistic and model-based alternative methods from the literature (LargeVis, Glove, Latent Space Position Model, probabilistic Correspondence Analysis, Stochastic Block Model) for nonlinear embedding via low dimensional positions.