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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
ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 7 months ago
An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoy...
ICDE
1997
IEEE
108views Database» more  ICDE 1997»
14 years 7 months ago
Titan: A High-Performance Remote Sensing Database
There are two major challenges for a high-performance remote-sensing database. First, it must provide low-latency retrieval of very large volumes of spatio-temporaldata. This requ...
Chialin Chang, Bongki Moon, Anurag Acharya, Carter...
SIGMOD
2011
ACM
283views Database» more  SIGMOD 2011»
12 years 8 months ago
iReduct: differential privacy with reduced relative errors
Prior work in differential privacy has produced techniques for answering aggregate queries over sensitive data in a privacypreserving way. These techniques achieve privacy by addi...
Xiaokui Xiao, Gabriel Bender, Michael Hay, Johanne...
PAMI
2006
127views more  PAMI 2006»
13 years 5 months ago
Incremental Nonlinear Dimensionality Reduction by Manifold Learning
Understanding the structure of multidimensional patterns, especially in unsupervised case, is of fundamental importance in data mining, pattern recognition and machine learning. Se...
Martin H. C. Law, Anil K. Jain