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» On High Dimensional Skylines
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PAMI
2006
127views more  PAMI 2006»
13 years 10 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain
ICPR
2010
IEEE
13 years 8 months ago
Verification Under Increasing Dimensionality
Verification decisions are often based on second order statistics estimated from a set of samples. Ongoing growth of computational resources allows for considering more and more fe...
Anne Hendrikse, Raymond N. J. Veldhuis, Luuk J. Sp...
CVPR
2007
IEEE
14 years 12 months ago
Regularized Mixed Dimensionality and Density Learning in Computer Vision
A framework for the regularized estimation of nonuniform dimensionality and density in high dimensional data is introduced in this work. This leads to learning stratifications, th...
Gloria Haro, Gregory Randall, Guillermo Sapiro
IROS
2007
IEEE
119views Robotics» more  IROS 2007»
14 years 4 months ago
Dimensionality reduction for hand-independent dexterous robotic grasping
— In this paper, we build upon recent advances in neuroscience research which have shown that control of the human hand during grasping is dominated by movement in a configurati...
Matei T. Ciocarlie, Corey Goldfeder, Peter K. Alle...
BMCBI
2008
141views more  BMCBI 2008»
13 years 10 months ago
Alternative contingency table measures improve the power and detection of multifactor dimensionality reduction
Background: Multifactor Dimensionality Reduction (MDR) has been introduced previously as a non-parametric statistical method for detecting gene-gene interactions. MDR performs a d...
William S. Bush, Todd L. Edwards, Scott M. Dudek, ...