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ICDE
2004
IEEE
14 years 8 months ago
2004
IEEE
Recent advances in research fields like multimedia and bioinformatics have brought about a new generation of hyper-dimensional databases which can contain hundreds or even thousan...
CVPR
2006
IEEE
14 years 9 months ago
2006
IEEE
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
EMO
2006
Springer
13 years 11 months ago
2006
Springer
1 In most real world optimization problems several optimization goals have to be considered in parallel. For this reason, there has been a growing interest in Multi-Objective Optim...
PAKDD
2009
ACM
14 years 2 months ago
2009
ACM
Abstract. Clustering high dimensional data with sparse features is challenging because pairwise distances between data items are not informative in high dimensional space. To addre...
ICML
2004
IEEE
14 years 27 days ago
2004
IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...