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» Manifold Learning: The Price of Normalization
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CVPR
2007
IEEE
14 years 6 months ago
Connecting the Out-of-Sample and Pre-Image Problems in Kernel Methods
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...
Pablo Arias, Gregory Randall, Guillermo Sapiro
ML
2010
ACM
193views Machine Learning» more  ML 2010»
12 years 11 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...
CORR
2010
Springer
136views Education» more  CORR 2010»
13 years 3 months ago
Viewpoints: A high-performance high-dimensional exploratory data analysis tool
Scientific data sets continue to increase in both size and complexity. In the past, dedicated graphics systems at supercomputing centers were required to visualize large data sets,...
Paul R. Gazis, C. Levit, Michael J. Way