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» On the Optimality of the Dimensionality Reduction Method
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AAAI
2010
14 years 7 months ago
Non-I.I.D. Multi-Instance Dimensionality Reduction by Learning a Maximum Bag Margin Subspace
Multi-instance learning, as other machine learning tasks, also suffers from the curse of dimensionality. Although dimensionality reduction methods have been investigated for many ...
Wei Ping, Ye Xu, Kexin Ren, Chi-Hung Chi, Shen Fur...
79
Voted
ICML
2007
IEEE
15 years 10 months ago
Regression on manifolds using kernel dimension reduction
We study the problem of discovering a manifold that best preserves information relevant to a nonlinear regression. Solving this problem involves extending and uniting two threads ...
Jens Nilsson, Fei Sha, Michael I. Jordan
SDM
2010
SIAM
165views Data Mining» more  SDM 2010»
14 years 11 months ago
Direct Density Ratio Estimation with Dimensionality Reduction
Methods for directly estimating the ratio of two probability density functions without going through density estimation have been actively explored recently since they can be used...
Masashi Sugiyama, Satoshi Hara, Paul von Büna...
ICDE
2002
IEEE
91views Database» more  ICDE 2002»
15 years 2 months ago
Lossy Reduction for Very High Dimensional Data
We consider the use of data reduction techniques for the problem of approximate query answering. We focus on applications for which accurate answers to selective queries are requi...
Chris Jermaine, Edward Omiecinski
CVPR
2006
IEEE
15 years 11 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun