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» Near Optimal Dimensionality Reductions That Preserve Volumes
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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
TSMC
2010
14 years 4 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer
CIKM
2007
Springer
15 years 3 months ago
Regularized locality preserving indexing via spectral regression
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
Deng Cai, Xiaofei He, Wei Vivian Zhang, Jiawei Han
PR
2010
145views more  PR 2010»
14 years 8 months ago
Graph-optimized locality preserving projections
Locality preserving projections (LPP) is a typical graph-based dimensionality reduction (DR) method, and has been successfully applied in many practical problems such as face recog...
Limei Zhang, Lishan Qiao, Songcan Chen
NIPS
2007
14 years 11 months ago
Colored Maximum Variance Unfolding
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
Le Song, Alex J. Smola, Karsten M. Borgwardt, Arth...