165 search results - page 16 / 33 » Adaptive dimension reduction for clustering high dimensional... |
ICASSP
2008
IEEE
15 years 6 months ago
2008
IEEE
Local intrinsic dimension estimation has been shown to be useful for many tasks such as image segmentation, anomaly detection, and de-biasing global dimension estimates. Of partic...
ADC
2003
Springer
15 years 5 months ago
2003
Springer
Minkowski-sum cost model indicates that balanced data partitioning is not beneficial for high dimensional data. Thus we study several unbalanced partitioning methods and propose ...
132
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VLDB
2000
ACM
15 years 3 months ago
2000
ACM
Nearest neighbor search in high dimensional spaces is an interesting and important problem which is relevant for a wide variety of novel database applications. As recent results s...
NIPS
2004
15 years 1 months ago
2004
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
175
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SIGMOD
2006
ACM
15 years 12 months ago
2006
ACM
Given a d-dimensional data set, a point p dominates another point q if it is better than or equal to q in all dimensions and better than q in at least one dimension. A point is a ...