22 search results - page 2 / 5 » A survey of multilinear subspace learning for tensor data |
ECCV
2010
Springer
13 years 7 months ago
2010
Springer
Confronted with the high-dimensional tensor-like visual data, we derive a method for the decomposition of an observed tensor into a low-dimensional structure plus unbounded but spa...
ICASSP
2008
IEEE
13 years 11 months ago
2008
IEEE
Dimensionality reduction (DR) is a major issue to improve the efficiency of the classifiers in Hyperspectral images (HSI). Recently, the independent component analysis (ICA) app...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
A representative subspace is significant for image analysis, while the corresponding techniques often suffer from the curse of dimensionality dilemma. In this paper, we propose a ...
AAAI
2010
13 years 1 months ago
2010
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
We present a subspace learning method, called Local Discriminant Embedding with Tensor representation (LDET), that addresses simultaneously the generalization and data representat...