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» Linear Dependent Dimensionality Reduction
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SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 5 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
ICASSP
2011
IEEE
12 years 9 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
CVPR
2009
IEEE
15 years 14 days ago
Rank Priors for Continuous Non-Linear Dimensionality Reduction
Non-linear dimensionality reductionmethods are powerful techniques to deal with high-dimensional datasets. However, they often are susceptible to local minima and perform poorly ...
Andreas Geiger (Karlsruhe Institute of Technology)...