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» Genetic-Fuzzy Modeling on High Dimensional Spaces
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ICCV
2009
IEEE
15 years 28 days ago
Dimensionality Reduction and Principal Surfaces via Kernel Map Manifolds
We present a manifold learning approach to dimensionality reduction that explicitly models the manifold as a mapping from low to high dimensional space. The manifold is represen...
Samuel Gerber, Tolga Tasdizen, Ross Whitaker
CGF
2010
144views more  CGF 2010»
13 years 8 months ago
Dynamic Multi-View Exploration of Shape Spaces
Statistical shape modeling is a widely used technique for the representation and analysis of the shapes and shape variations present in a population. A statistical shape model mod...
Stef Busking, Charl P. Botha, Frits H. Post
ICTAI
2005
IEEE
14 years 1 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
EUSFLAT
2003
132views Fuzzy Logic» more  EUSFLAT 2003»
13 years 9 months ago
Modeling high interest areas in descriptive TS fuzzy rule based systems
A descriptive Takagi-Sugeno fuzzy rule based system suffers under the curse of dimensionality since the number of rules is equal to a fuzzy system with a fully filled up decision...
Ingo Renners, Adolf Grauel
ICPR
2008
IEEE
14 years 2 months ago
Manifold denoising with Gaussian Process Latent Variable Models
For a finite set of points lying on a lower dimensional manifold embedded in a high-dimensional data space, algorithms have been developed to study the manifold structure. Howeve...
Yan Gao, Kap Luk Chan, Wei-Yun Yau