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» Comparing Massive High-Dimensional Data Sets
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JMLR
2006
206views more  JMLR 2006»
13 years 7 months ago
New Algorithms for Efficient High-Dimensional Nonparametric Classification
This paper is about non-approximate acceleration of high-dimensional nonparametric operations such as k nearest neighbor classifiers. We attempt to exploit the fact that even if w...
Ting Liu, Andrew W. Moore, Alexander G. Gray
VLDB
1999
ACM
224views Database» more  VLDB 1999»
13 years 11 months ago
Optimal Grid-Clustering: Towards Breaking the Curse of Dimensionality in High-Dimensional Clustering
Many applications require the clustering of large amounts of high-dimensional data. Most clustering algorithms, however, do not work e ectively and e ciently in highdimensional sp...
Alexander Hinneburg, Daniel A. Keim
ICDE
1998
IEEE
142views Database» more  ICDE 1998»
14 years 8 months ago
High Dimensional Similarity Joins: Algorithms and Performance Evaluation
Current data repositories include a variety of data types, including audio, images and time series. State of the art techniques for indexing such data and doing query processing r...
Nick Koudas, Kenneth C. Sevcik
EDBT
2006
ACM
182views Database» more  EDBT 2006»
14 years 7 months ago
On High Dimensional Skylines
In many decision-making applications, the skyline query is frequently used to find a set of dominating data points (called skyline points) in a multidimensional dataset. In a high-...
Chee Yong Chan, H. V. Jagadish, Kian-Lee Tan, Anth...
ICDE
1998
IEEE
163views Database» more  ICDE 1998»
14 years 8 months ago
Fast Nearest Neighbor Search in High-Dimensional Space
Similarity search in multimedia databases requires an efficient support of nearest-neighbor search on a large set of high-dimensional points as a basic operation for query process...
Stefan Berchtold, Bernhard Ertl, Daniel A. Keim, H...