62 search results - page 2 / 13 » A Beta-Mixture Model for Dimensionality Reduction, Sample Cl... |
ICIP
2005
IEEE
14 years 6 months ago
2005
IEEE
We study the use of kernel subspace methods that learn low-dimensional subspace representations for classification tasks. In particular, we propose a new method called kernel weigh...
SAC
2006
ACM
13 years 11 months ago
2006
ACM
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
PAMI
2008
13 years 4 months ago
2008
We present a novel probabilistic latent variable model to perform linear dimensionality reduction on data sets which contain clusters. We prove that the maximum likelihood solution...
SADM
2010
12 years 11 months ago
2010
This paper is concerned with classifying high dimensional data into one of two categories. In various settings, such as when dealing with fMRI and microarray data, the number of v...
ECCV
2004
Springer
14 years 6 months ago
2004
Springer
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...