59 search results - page 8 / 12 » Sparse Higher-Order Principal Components Analysis |
CVPR
2005
IEEE
15 years 26 days 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 ...
CSDA
2008
13 years 11 months ago
2008
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
ICML
2010
IEEE
13 years 11 months ago
2010
IEEE
We investigate the sparse eigenvalue problem which arises in various fields such as machine learning and statistics. Unlike standard approaches relying on approximation of the l0n...
AAAI
2008
14 years 1 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
ICDM
2007
IEEE
14 years 2 months ago
2007
IEEE
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...