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» Dimensionality reduction and generalization
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140
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CORR
2012
Springer
198views Education» more  CORR 2012»
13 years 11 months ago
Lipschitz Parametrization of Probabilistic Graphical Models
We show that the log-likelihood of several probabilistic graphical models is Lipschitz continuous with respect to the ￿p-norm of the parameters. We discuss several implications ...
Jean Honorio
135
Voted
IGARSS
2009
15 years 1 months ago
Classification Performance of Random-projection-based Dimensionality Reduction of Hyperspectral Imagery
High-dimensional data such as hyperspectral imagery is traditionally acquired in full dimensionality before being reduced in dimension prior to processing. Conventional dimensiona...
James E. Fowler, Qian Du, Wei Zhu, Nicolas H. Youn...
143
Voted
CIKM
2008
Springer
15 years 5 months ago
On low dimensional random projections and similarity search
Random projection (RP) is a common technique for dimensionality reduction under L2 norm for which many significant space embedding results have been demonstrated. However, many si...
Yu-En Lu, Pietro Liò, Steven Hand
148
Voted
SMA
2005
ACM
132views Solid Modeling» more  SMA 2005»
15 years 9 months ago
Simplified engineering analysis via medial mesh reduction
Numerous simplification methods have been proposed for speeding up engineering analysis/ simulation. A recently proposed medial axis reduction is one such method, that is particul...
Murari Sinha, Krishnan Suresh
149
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Compressed classification of observation sets with linear subspace embeddings
We consider the problem of classification of a pattern from multiple compressed observations that are collected in a sensor network. In particular, we exploit the properties of r...
Dorina Thanou, Pascal Frossard