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» The intrinsic dimensionality of graphs
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IVC
2007
184views more  IVC 2007»
13 years 9 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
AUTOMATICA
2007
88views more  AUTOMATICA 2007»
13 years 10 months ago
Three and higher dimensional autonomous formations: Rigidity, persistence and structural persistence
In this paper, we generalize the notion of persistence, which has been originally introduced for two-dimensional formations, to Rd for d 3, seeking to provide a theoretical framew...
Changbin Yu, Julien M. Hendrickx, Baris Fidan, Bri...
SPDP
1991
IEEE
14 years 1 months ago
Fault-tolerant meshes with minimal numbers of spares
This paper presents several techniques for adding fault-tolerance to distributed memory parallel computers. More formally, given a target graph with n nodes, we create a fault-tol...
Jehoshua Bruck, Robert Cypher, Ching-Tien Ho
ICPR
2008
IEEE
14 years 11 months ago
Multiclass spectral clustering based on discriminant analysis
Many existing spectral clustering algorithms share a conventional graph partitioning criterion: normalized cuts (NC). However, one problem with NC is that it poorly captures the g...
Xi Li, Zhongfei Zhang, Yanguo Wang, Weiming Hu
WEBI
2010
Springer
13 years 7 months ago
DSP: Robust Semi-supervised Dimensionality Reduction Using Dual Subspace Projections
High-dimensional data usually incur learning deficiencies and computational difficulties. We present a novel semi-supervised dimensionality reduction technique that embeds high-dim...
Su Yan, Sofien Bouaziz, Dongwon Lee