165 search results - page 28 / 33 » Adaptive dimension reduction for clustering high dimensional... |
ICASSP
2010
IEEE
13 years 8 months ago
2010
IEEE
Flow cytometry (FC) is a powerful technology for rapid multivariate analysis and functional discrimination of cells. Current FC platforms generate large, high-dimensional datasets...
ICASSP
2011
IEEE
13 years 8 days ago
2011
IEEE
The Restricted Isometry Property (RIP) is an important concept in compressed sensing. It is well known that many random matrices satisfy the RIP with high probability, whenever th...
CVPR
2007
IEEE
14 years 10 months ago
2007
IEEE
The success of tensor-based subspace learning depends heavily on reducing correlations along the column vectors of the mode-k flattened matrix. In this work, we study the problem ...
ESANN
2006
13 years 10 months ago
2006
The Self-Organizing map (SOM), a powerful method for data mining and cluster extraction, is very useful for processing data of high dimensionality and complexity. Visualization met...
PREMI
2005
Springer
14 years 2 months ago
2005
Springer
Images constitute data that lives in a very high dimensional space, typically of the order of hundred thousand dimensions. Drawing inferences from data of such high dimensions soon...