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» REDUS: finding reducible subspaces in high dimensional data
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EDBT
2006
ACM
182views Database» more  EDBT 2006»
14 years 4 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...
CVPR
2008
IEEE
14 years 6 months ago
Dimensionality reduction using covariance operator inverse regression
We consider the task of dimensionality reduction for regression (DRR) whose goal is to find a low dimensional representation of input covariates, while preserving the statistical ...
Minyoung Kim, Vladimir Pavlovic
KDD
2005
ACM
142views Data Mining» more  KDD 2005»
14 years 5 months ago
Towards exploratory test instance specific algorithms for high dimensional classification
In an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior...
Charu C. Aggarwal
VLDB
2007
ACM
174views Database» more  VLDB 2007»
14 years 5 months ago
An adaptive and dynamic dimensionality reduction method for high-dimensional indexing
Abstract The notorious "dimensionality curse" is a wellknown phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well-known approa...
Heng Tao Shen, Xiaofang Zhou, Aoying Zhou
ICDE
2002
IEEE
164views Database» more  ICDE 2002»
14 years 6 months ago
Towards Meaningful High-Dimensional Nearest Neighbor Search by Human-Computer Interaction
Nearest Neighbor search is an important and widely used problem in a number of important application domains. In many of these domains, the dimensionality of the data representati...
Charu C. Aggarwal