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ICML
2006
IEEE
14 years 8 months ago
A duality view of spectral methods for dimensionality reduction
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
Lin Xiao, Jun Sun 0003, Stephen P. Boyd
GBRPR
2009
Springer
14 years 2 months ago
Inexact Matching of Large and Sparse Graphs Using Laplacian Eigenvectors
In this paper we propose an inexact spectral matching algorithm that embeds large graphs on a low-dimensional isometric space spanned by a set of eigenvectors of the graph Laplacia...
David Knossow, Avinash Sharma, Diana Mateus, Radu ...
ICCV
2007
IEEE
14 years 9 months ago
Spectral Regression for Efficient Regularized Subspace Learning
Subspace learning based face recognition methods have attracted considerable interests in recent years, including Principal Component Analysis (PCA), Linear Discriminant Analysis ...
Deng Cai, Xiaofei He, Jiawei Han
SIAMSC
2008
131views more  SIAMSC 2008»
13 years 7 months ago
Gramian-Based Model Reduction for Data-Sparse Systems
Model order reduction (MOR) is common in simulation, control and optimization of complex dynamical systems arising in modeling of physical processes and in the spatial discretizati...
Ulrike Baur, Peter Benner
CDC
2009
IEEE
114views Control Systems» more  CDC 2009»
13 years 10 months ago
Parametric model order reduction accelerated by subspace recycling
Abstract-- Many model order reduction methods for parameterized systems need to construct a projection matrix V which requires computing several moment matrices of the parameterize...
Lihong Feng, Peter Benner, Jan G. Korvink