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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 5 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 5 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 5 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»
13 years 8 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 4 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