785 search results - page 43 / 157 » Semi-Supervised Dimensionality Reduction |
135
Voted
APVIS
2010
15 years 5 months ago
2010
Information visualization is essential in making sense out of large data sets. Often, high-dimensional data are visualized as a collection of points in 2-dimensional space through...
132
click to vote
AUSAI
2006
Springer
15 years 7 months ago
2006
Springer
In this paper, we propose the Kernel Laplacian Eigenmaps for nonlinear dimensionality reduction. This method can be extended to any structured input beyond the usual vectorial data...
145
click to vote
CIARP
2006
Springer
15 years 7 months ago
2006
Springer
Feature selection and dimensionality reduction are crucial research fields in pattern recognition. This work presents the application of a novel technique on dimensionality reducti...
148
click to vote
BMVC
2010
15 years 1 months ago
2010
We present a framework for the reduction of dimensionality of a data set via manifold learning. Using the building blocks of local hyperplanes we show how a global manifold can be...
114
Voted
ICIP
2010
IEEE
15 years 1 months ago
2010
IEEE
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...