69 search results - page 8 / 14 » Unsupervised Feature Selection in High Dimensional Spaces an... |
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
In Kernel Fisher discriminant analysis (KFDA), we carry out Fisher linear discriminant analysis in a high dimensional feature space defined implicitly by a kernel. The performance...
IDA
2003
Springer
15 years 2 months ago
2003
Springer
For a mobile robot to act autonomously, it must be able to construct a model of its interaction with the environment. Oates et al. developed an unsupervised learning method that pr...
105
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DATAMINE
2006
14 years 9 months ago
2006
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
ICCV
2011
IEEE
13 years 9 months ago
2011
IEEE
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
105
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SAC
2006
ACM
15 years 3 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...