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» Sparse Unsupervised Dimensionality Reduction Algorithms
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FGR
2006
IEEE
217views Biometrics» more  FGR 2006»
14 years 1 months ago
Face Recognition with Image Sets Using Hierarchically Extracted Exemplars from Appearance Manifolds
An unsupervised nonparametric approach is proposed to automatically extract representative face samples (exemplars) from a video sequence or an image set for multipleshot face rec...
Wei Fan, Dit-Yan Yeung
SIGIR
2005
ACM
14 years 1 months ago
Multi-label informed latent semantic indexing
Latent semantic indexing (LSI) is a well-known unsupervised approach for dimensionality reduction in information retrieval. However if the output information (i.e. category labels...
Kai Yu, Shipeng Yu, Volker Tresp
AAAI
2008
13 years 10 months ago
Sparse Projections over Graph
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
Deng Cai, Xiaofei He, Jiawei Han
TSP
2008
151views more  TSP 2008»
13 years 7 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
CVPR
2007
IEEE
14 years 9 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal