# Symmetric Generative Methods and tSNE: A Short Survey

### Rodolphe Priam

#### 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.

Download#### Paper Citation

#### in Harvard Style

Priam R. (2018). **Symmetric Generative Methods and tSNE: A Short Survey**.In *Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,* ISBN 978-989-758-289-9, pages 356-363. DOI: 10.5220/0006684303560363

#### in Bibtex Style

@conference{ivapp18,

author={Rodolphe Priam},

title={Symmetric Generative Methods and tSNE: A Short Survey},

booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,},

year={2018},

pages={356-363},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0006684303560363},

isbn={978-989-758-289-9},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: IVAPP,

TI - Symmetric Generative Methods and tSNE: A Short Survey

SN - 978-989-758-289-9

AU - Priam R.

PY - 2018

SP - 356

EP - 363

DO - 10.5220/0006684303560363