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» High-dimensional labeled data analysis with Gabriel graphs
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ICML
2006
IEEE
14 years 6 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
ICASSP
2010
IEEE
13 years 6 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
CIKM
2005
Springer
13 years 11 months ago
Compact reachability labeling for graph-structured data
Testing reachability between nodes in a graph is a well-known problem with many important applications, including knowledge representation, program analysis, and more recently, bi...
Hao He, Haixun Wang, Jun Yang 0001, Philip S. Yu
IPMI
2005
Springer
14 years 6 months ago
Analysis of Event-Related fMRI Data Using Diffusion Maps
The blood oxygen level-dependent (BOLD) signal in response to brief periods of stimulus can be detected using event-related functional magnetic resonance imaging (ER-fMRI). In this...
François G. Meyer, Xilin Shen
IPMI
2003
Springer
14 years 6 months ago
Permutation Tests for Classification: Towards Statistical Significance in Image-Based Studies
Abstract. Estimating statistical significance of detected differences between two groups of medical scans is a challenging problem due to the high dimensionality of the data and th...
Polina Golland, Bruce Fischl