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PKDD
2009
Springer
120views Data Mining» more  PKDD 2009»
14 years 2 months ago
Variational Graph Embedding for Globally and Locally Consistent Feature Extraction
Existing feature extraction methods explore either global statistical or local geometric information underlying the data. In this paper, we propose a general framework to learn fea...
Shuang-Hong Yang, Hongyuan Zha, Shaohua Kevin Zhou...
ISBI
2004
IEEE
14 years 8 months ago
Local Feature Matching Using Entropic Graphs
We present a general framework for image discrimination based on identifying small, localized differences between images. Our novel matching scheme is based on an alternate inform...
Huzefa Neemuchwala, Alfred O. Hero, Paul L. Carson...
PRL
2010
188views more  PRL 2010»
13 years 5 months ago
Sparsity preserving discriminant analysis for single training image face recognition
: Single training image face recognition is one of main challenges to appearance-based pattern recognition techniques. Many classical dimensionality reduction methods such as LDA h...
Lishan Qiao, Songcan Chen, Xiaoyang Tan
NIPS
2003
13 years 8 months ago
Discriminative Fields for Modeling Spatial Dependencies in Natural Images
In this paper we present Discriminative Random Fields (DRF), a discriminative framework for the classification of natural image regions by incorporating neighborhood spatial depe...
Sanjiv Kumar, Martial Hebert
ICML
2006
IEEE
14 years 8 months ago
Discriminative cluster analysis
Clustering is one of the most widely used statistical tools for data analysis. Among all existing clustering techniques, k-means is a very popular method because of its ease of pr...
Fernando De la Torre, Takeo Kanade