98 search results - page 10 / 20 » On Point Sampling Versus Space Sampling for Dimensionality R... |
IV
2007
IEEE
14 years 1 months ago
2007
IEEE
High-dimensional data is, by its nature, difficult to visualise. Many current techniques involve reducing the dimensionality of the data, which results in a loss of information. ...
CORR
2006
Springer
13 years 7 months ago
2006
Springer
Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the subm...
JMLR
2012
11 years 10 months ago
2012
In this paper, we propose a second order optimization method to learn models where both the dimensionality of the parameter space and the number of training samples is high. In ou...
IEEEMM
2007
13 years 7 months ago
2007
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
IROS
2009
IEEE
14 years 2 months ago
2009
IEEE
— In this paper we present a new approach for labeling 3D points with different geometric surface primitives using a novel feature descriptor – the Fast Point Feature Histogram...