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» A Riemannian approach to graph embedding
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BMCBI
2006
202views more  BMCBI 2006»
13 years 7 months ago
Spectral embedding finds meaningful (relevant) structure in image and microarray data
Background: Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing ...
Brandon W. Higgs, Jennifer W. Weller, Jeffrey L. S...
EUROCOLT
1995
Springer
13 years 11 months ago
The structure of intrinsic complexity of learning
Limiting identification of r.e. indexes for r.e. languages (from a presentation of elements of the language) and limiting identification of programs for computable functions (fr...
Sanjay Jain, Arun Sharma
ML
2010
ACM
193views Machine Learning» more  ML 2010»
13 years 2 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
INFOVIS
2005
IEEE
14 years 1 months ago
Visualization of Graphs with Associated Timeseries Data
The most common approach to support analysis of graphs with associated time series data include: overlay of data on graph vertices for one timepoint at a time by manipulating a vi...
Purvi Saraiya, Peter Lee, Chris North
IPPS
2007
IEEE
14 years 2 months ago
A Multi-Level Parallel Implementation of a Program for Finding Frequent Patterns in a Large Sparse Graph
Graphs capture the essential elements of many problems broadly defined as searching or categorizing. With the rapid increase of data volumes from sensors, many application discipl...
Steve Reinhardt, George Karypis