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» Approximated Clustering of Distributed High-Dimensional Data
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TKDE
2011
332views more  TKDE 2011»
13 years 8 days ago
Adaptive Cluster Distance Bounding for High-Dimensional Indexing
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
Sharadh Ramaswamy, Kenneth Rose
PCM
2001
Springer
183views Multimedia» more  PCM 2001»
13 years 9 months ago
An Adaptive Index Structure for High-Dimensional Similarity Search
A practical method for creating a high dimensional index structure that adapts to the data distribution and scales well with the database size, is presented. Typical media descrip...
Peng Wu, B. S. Manjunath, Shivkumar Chandrasekaran
NIPS
2001
13 years 6 months ago
Estimating Car Insurance Premia: a Case Study in High-Dimensional Data Inference
Estimating insurance premia from data is a difficult regression problem for several reasons: the large number of variables, many of which are discrete, and the very peculiar shape...
Nicolas Chapados, Yoshua Bengio, Pascal Vincent, J...
MICAI
2005
Springer
13 years 10 months ago
Proximity Searching in High Dimensional Spaces with a Proximity Preserving Order
Abstract. Kernel based methods (such as k-nearest neighbors classifiers) for AI tasks translate the classification problem into a proximity search problem, in a space that is usu...
Edgar Chávez, Karina Figueroa, Gonzalo Nava...
VLDB
2000
ACM
229views Database» more  VLDB 2000»
13 years 9 months ago
Local Dimensionality Reduction: A New Approach to Indexing High Dimensional Spaces
Many emerging application domains require database systems to support efficient access over highly multidimensional datasets. The current state-of-the-art technique to indexing hi...
Kaushik Chakrabarti, Sharad Mehrotra