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ICML
2007
IEEE
14 years 9 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
SPEECH
1998
118views more  SPEECH 1998»
13 years 8 months ago
Dimensionality reduction of electropalatographic data using latent variable models
We consider the problem of obtaining a reduced dimension representation of electropalatographic (EPG) data. An unsupervised learning approach based on latent variable modelling is...
Miguel Á. Carreira-Perpiñán, ...
IRI
2007
IEEE
14 years 2 months ago
Enhancing Text Analysis via Dimensionality Reduction
Many applications require analyzing vast amounts of textual data, but the size and inherent noise of such data can make processing very challenging. One approach to these issues i...
David G. Underhill, Luke McDowell, David J. Marche...
VLDB
2000
ACM
229views Database» more  VLDB 2000»
14 years 2 days ago
Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
Kaushik Chakrabarti, Sharad Mehrotra
CVPR
2008
IEEE
14 years 10 months ago
Tensor reduction error analysis - Applications to video compression and classification
Tensor based dimensionality reduction has recently been extensively studied for computer vision applications. To our knowledge, however, there exist no rigorous error analysis on ...
Chris H. Q. Ding, Heng Huang, Dijun Luo