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» Non-Linear Dimensionality Reduction
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ICIP
2010
IEEE
15 years 2 months ago
Image analysis with regularized Laplacian eigenmaps
Many classes of image data span a low dimensional nonlinear space embedded in the natural high dimensional image space. We adopt and generalize a recently proposed dimensionality ...
Frank Tompkins, Patrick J. Wolfe
SAC
2005
ACM
15 years 10 months ago
Estimating manifold dimension by inversion error
Video and image datasets can often be described by a small number of parameters, even though each image usually consists of hundreds or thousands of pixels. This observation is of...
Shawn Martin, Alex Bäcker
COMPLIFE
2006
Springer
15 years 8 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...
DEXA
2006
Springer
190views Database» more  DEXA 2006»
15 years 8 months ago
High-Dimensional Similarity Search Using Data-Sensitive Space Partitioning
Abstract. Nearest neighbor search has a wide variety of applications. Unfortunately, the majority of search methods do not scale well with dimensionality. Recent efforts have been ...
Sachin Kulkarni, Ratko Orlandic
CSDA
2006
138views more  CSDA 2006»
15 years 4 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