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» Local Dimensionality Reduction
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FGR
2000
IEEE
181views Biometrics» more  FGR 2000»
15 years 2 months ago
Face Detection Using Mixtures of Linear Subspaces
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
14 years 11 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
SDM
2007
SIAM
108views Data Mining» more  SDM 2007»
14 years 11 months ago
Semi-Supervised Dimensionality Reduction
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
ACMSE
2005
ACM
15 years 3 months ago
Using nonlinear dimensionality reduction in 3D figure animation
This paper explores a method for re-sequencing an existing set of animation, specifically motion capture data, to generate new motion. Re-using animation is helpful in designing ...
A. Elizabeth Seward, Bobby Bodenheimer
ICMCS
2005
IEEE
79views Multimedia» more  ICMCS 2005»
15 years 3 months ago
Supervised semi-definite embedding for image manifolds
Semi-definite Embedding (SDE) has been a recently proposed to maximize the sum of pair wise squared distances between outputs while the input data and outputs are locally isometri...
Benyu Zhang, Jun Yan, Ning Liu, QianSheng Cheng, Z...