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» Semi-supervised nonlinear dimensionality reduction
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AAAI
2007
15 years 8 months ago
Isometric Projection
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
Deng Cai, Xiaofei He, Jiawei Han
192
Voted
PR
2008
129views more  PR 2008»
15 years 6 months ago
A comparison of generalized linear discriminant analysis algorithms
7 Linear discriminant analysis (LDA) is a dimension reduction method which finds an optimal linear transformation that maximizes the class separability. However, in undersampled p...
Cheong Hee Park, Haesun Park
200
Voted
AMDO
2006
Springer
15 years 10 months ago
Human Motion Synthesis by Motion Manifold Learning and Motion Primitive Segmentation
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
Chan-Su Lee, Ahmed M. Elgammal
ICCV
2011
IEEE
14 years 6 months ago
Kernel Non-Rigid Structure from Motion
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...
Paulo F. U. Gotardo, Aleix M. Martinez
ICPR
2008
IEEE
16 years 27 days ago
Clustering-based locally linear embedding
The locally linear embedding (LLE) algorithm is considered as a powerful method for the problem of nonlinear dimensionality reduction. In this paper, first, a new method called cl...
Kanghua Hui, Chunheng Wang