140 search results - page 13 / 28 » Dimensionality Reduction with Adaptive Kernels |
JMLR
2012
11 years 10 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
ESANN
2007
13 years 9 months ago
2007
We study dimensionality reduction or feature selection in text document categorization problem. We focus on the first step in building text categorization systems, that is the cho...
CGA
2005
13 years 7 months ago
2005
A novel Monte Carlo noise reduction operator is proposed in this paper. We apply and extend the standard bilateral filtering method and build a new local adaptive noise reduction k...
ICCV
2007
IEEE
14 years 9 months ago
2007
IEEE
A general methodology for noise reduction and contrast enhancement in very noisy image data with low dynamic range is presented. Video footage recorded in very dim light is especi...
NIPS
2004
13 years 8 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...