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» Cluster analysis of heterogeneous rank data
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CVPR
2012
IEEE
13 years 3 days ago
Fixed-rank representation for unsupervised visual learning
Subspace clustering and feature extraction are two of the most commonly used unsupervised learning techniques in computer vision and pattern recognition. State-of-theart technique...
Risheng Liu, Zhouchen Lin, Fernando De la Torre, Z...
DEXA
2007
Springer
154views Database» more  DEXA 2007»
15 years 3 months ago
Performance Oriented Schema Matching
Abstract. Semantic matching of schemas in heterogeneous data sharing systems is time consuming and error prone. Existing mapping tools employ semi-automatic techniques for mapping ...
Khalid Saleem, Zohra Bellahsene, Ela Hunt
PAMI
2012
13 years 4 days ago
A Least-Squares Framework for Component Analysis
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
Fernando De la Torre
PDPTA
2010
14 years 7 months ago
Collecting Sensor Data for High-Performance Computing: A Case-study
- Many research questions remain open with regard to improving reliability in exascale systems. Among others, statistics-based analysis has been used to find anomalies, to isolate ...
Line C. Pouchard, Jonathan D. Dobson, Stephen W. P...
BMCBI
2010
92views more  BMCBI 2010»
14 years 9 months ago
Integrating gene expression and GO classification for PCA by preclustering
Background: Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per g...
Jorn R. de Haan, Ester Piek, René C. van Sc...