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COMPLIFE
2006
Springer
13 years 9 months ago
Set-Oriented Dimension Reduction: Localizing Principal Component Analysis Via Hidden Markov Models
We present a method for simultaneous dimension reduction and metastability analysis of high dimensional time series. The approach is based on the combination of hidden Markov model...
Illia Horenko, Johannes Schmidt-Ehrenberg, Christo...
CSDA
2006
138views more  CSDA 2006»
13 years 5 months ago
Automatic dimensionality selection from the scree plot via the use of profile likelihood
Most dimension reduction techniques produce ordered coordinates so that only the first few coordinates need be considered in subsequent analyses. The choice of how many coordinate...
Mu Zhu, Ali Ghodsi
PODS
2001
ACM
190views Database» more  PODS 2001»
14 years 5 months ago
On the Effects of Dimensionality Reduction on High Dimensional Similarity Search
The dimensionality curse has profound e ects on the effectiveness of high-dimensional similarity indexing from the performance perspective. One of the well known techniques for im...
Charu C. Aggarwal
CVPR
2008
IEEE
14 years 7 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic