79 search results - page 6 / 16 » Automatic configuration of spectral dimensionality reduction... |
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
AIPR
2003
IEEE
14 years 27 days ago
2003
IEEE
Although hyperspectral images provide abundant information about objects, their high dimensionality also substantially increases computational burden. Dimensionality reduction off...
ICPR
2010
IEEE
13 years 10 months ago
2010
IEEE
—A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach,...
ICML
2009
IEEE
14 years 8 months ago
2009
IEEE
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
BMCBI
2006
13 years 7 months ago
2006
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...