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PAMI
2006
141views more  PAMI 2006»
13 years 7 months ago
Diffusion Maps and Coarse-Graining: A Unified Framework for Dimensionality Reduction, Graph Partitioning, and Data Set Parameter
We provide evidence that non-linear dimensionality reduction, clustering and data set parameterization can be solved within one and the same framework. The main idea is to define ...
Stéphane Lafon, Ann B. Lee
ICDE
2010
IEEE
222views Database» more  ICDE 2010»
13 years 6 months ago
Finding Clusters in subspaces of very large, multi-dimensional datasets
Abstract— We propose the Multi-resolution Correlation Cluster detection (MrCC), a novel, scalable method to detect correlation clusters able to analyze dimensional data in the ra...
Robson Leonardo Ferreira Cordeiro, Agma J. M. Trai...
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 8 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
HPCA
2006
IEEE
14 years 1 months ago
Increasing the cache efficiency by eliminating noise
Caches are very inefficiently utilized because not all the excess data fetched into the cache, to exploit spatial locality, is utilized. We define cache utilization as the percent...
Prateek Pujara, Aneesh Aggarwal
SIGMOD
1998
ACM
142views Database» more  SIGMOD 1998»
13 years 12 months ago
Dimensionality Reduction for Similarity Searching in Dynamic Databases
Databases are increasingly being used to store multi-media objects such as maps, images, audio and video. Storage and retrieval of these objects is accomplished using multi-dimens...
Kothuri Venkata Ravi Kanth, Divyakant Agrawal, Amb...