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PAMI
2007
102views more  PAMI 2007»
13 years 9 months ago
Feature Subset Selection and Ranking for Data Dimensionality Reduction
—A new unsupervised forward orthogonal search (FOS) algorithm is introduced for feature selection and ranking. In the new algorithm, features are selected in a stepwise way, one ...
Hua-Liang Wei, Stephen A. Billings
SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
13 years 11 months ago
The Generalized Dimensionality Reduction Problem
The dimensionality reduction problem has been widely studied in the database literature because of its application for concise data representation in a variety of database applica...
Charu C. Aggarwal
IS
2008
13 years 10 months ago
A dimensionality reduction technique for efficient time series similarity analysis
We propose a dimensionality reduction technique for time series analysis that significantly improves the efficiency and accuracy of similarity searches. In contrast to piecewise c...
Qiang Wang, Vasileios Megalooikonomou
SDM
2004
SIAM
162views Data Mining» more  SDM 2004»
13 years 11 months ago
Subspace Clustering of High Dimensional Data
Clustering suffers from the curse of dimensionality, and similarity functions that use all input features with equal relevance may not be effective. We introduce an algorithm that...
Carlotta Domeniconi, Dimitris Papadopoulos, Dimitr...
SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 10 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal