@InProceedings{BarbosaNona:2017:PrSt,
author = "Barbosa, Adriano Oliveira and Nonato, Luis Gustavo",
affiliation = "ICMC-USP/FACET-UFGD and ICMC-USP",
title = "Visualization, kernels and subspaces: a practical study",
booktitle = "Proceedings...",
year = "2017",
editor = "Torchelsen, Rafael Piccin and Nascimento, Erickson Rangel do and
Panozzo, Daniele and Liu, Zicheng and Farias, Myl{\`e}ne and
Viera, Thales and Sacht, Leonardo and Ferreira, Nivan and Comba,
Jo{\~a}o Luiz Dihl and Hirata, Nina and Schiavon Porto, Marcelo
and Vital, Creto and Pagot, Christian Azambuja and Petronetto,
Fabiano and Clua, Esteban and Cardeal, Fl{\'a}vio",
organization = "Conference on Graphics, Patterns and Images, 30. (SIBGRAPI)",
publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
address = "Porto Alegre",
keywords = "kernel methods, subspace clustering, multidimensional projection,
visualization.",
abstract = "Data involved in real applications are usually spread around in
distinct subspaces which may have different dimensions. We would
like to study how the subspace structure information can be used
to improve visualization tasks. On the other hand, what if the
data is tangled in this high-dimensional space, how to visualize
its patterns or how to accomplish classification tasks? This paper
presents an study for both problems pointed out above. For the
former, we use subspace clustering techniques to define, when it
exists, a subspace structure, studying how this information can be
used to support visualization tasks based on multidimensional
projections. For the latter problem we employ kernel methods, well
known in the literature, as a tool to assist visualization tasks.
We use a similarity measure given by the kernel to develop a
completely new multidimensional projection technique capable of
dealing with data embedded in the implicit feature space defined
by the kernel.",
conference-location = "Niter{\'o}i, RJ, Brazil",
conference-year = "17-20 Oct. 2017",
language = "en",
ibi = "8JMKD3MGPAW/3PJ5RDH",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3PJ5RDH",
targetfile = "compressed.pdf",
urlaccessdate = "2024, May 02"
}