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» On k-Anonymity and the Curse of Dimensionality
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ALENEX
2001
105views Algorithms» more  ALENEX 2001»
13 years 11 months ago
A Probabilistic Spell for the Curse of Dimensionality
Range searches in metric spaces can be very di cult if the space is \high dimensional", i.e. when the histogram of distances has a large mean and a small variance. The so-cal...
Edgar Chávez, Gonzalo Navarro
ICDE
2000
IEEE
120views Database» more  ICDE 2000»
14 years 11 months ago
Deflating the Dimensionality Curse Using Multiple Fractal Dimensions
Nearest neighbor queries are important in many settings, including spatial databases (Find the k closest cities) and multimedia databases (Find the k most similar images). Previou...
Bernd-Uwe Pagel, Flip Korn, Christos Faloutsos
ICDE
2007
IEEE
165views Database» more  ICDE 2007»
14 years 11 months ago
On Randomization, Public Information and the Curse of Dimensionality
A key method for privacy preserving data mining is that of randomization. Unlike k-anonymity, this technique does not include public information in the underlying assumptions. In ...
Charu C. Aggarwal
SIGMOD
1998
ACM
117views Database» more  SIGMOD 1998»
14 years 2 months ago
The Pyramid-Technique: Towards Breaking the Curse of Dimensionality
In this paper, we propose the Pyramid-Technique, a new indexing method for high-dimensional data spaces. The PyramidTechnique is highly adapted to range query processing using the...
Stefan Berchtold, Christian Böhm, Hans-Peter ...
CGF
2002
135views more  CGF 2002»
13 years 9 months ago
Slow Growing Subdivision (SGS) in Any Dimension: Towards Removing the Curse of Dimensionality
In recent years subdivision methods have been one of the most successful techniques applied to the multi-resolution representation and visualization of surface meshes. Extension t...
Valerio Pascucci