JMLR
2010
12 years 11 months ago
2010
We consider the problem of tactile discrimination, with the goal of estimating an underlying state parameter in a sequential setting. If the data is continuous and highdimensional...
TMI
2010
13 years 2 months ago
2010
Abstract—Interpolation is the means by which a continuouslydefined model is fit to discrete data samples. When the data samples are exempt of noise, it seems desirable to build...
PAMI
2007
13 years 4 months ago
2007
This paper considers the problem of dimensionality reduction by orthogonal projection techniques. The main feature of the proposed techniques is that they attempt to preserve both...
CORR
2000
Springer
13 years 4 months ago
2000
Springer
While Kolmogorov complexity is the accepted absolute measure of information content of an individual finite object, a similarly absolute notion is needed for the relation between a...
ICANN
2009
Springer
13 years 9 months ago
2009
Springer
Abstract. Many applications of machine learning involve sparse highdimensional data, where the number of input features is (much) larger than the number of data samples, d n. Predi...
CAIP
2005
Springer
13 years 10 months ago
2005
Springer
Non-parametric data representation can be done by means of a potential function. This paper introduces a methodology for finding modes of the potential function. Two different me...
ICDM
2005
IEEE
13 years 10 months ago
2005
IEEE
— Orthogonal Neighborhood Preserving Projections (ONPP) is a linear dimensionality reduction technique which attempts to preserve both the intrinsic neighborhood geometry of the ...
CVPR
2008
IEEE
14 years 6 months ago
2008
IEEE
Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...