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AAAI
2010
15 years 8 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
CVPR
2009
IEEE
17 years 1 months ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...
ICDE
2006
IEEE
194views Database» more  ICDE 2006»
16 years 8 months ago
The Gauss-Tree: Efficient Object Identification in Databases of Probabilistic Feature Vectors
In applications of biometric databases the typical task is to identify individuals according to features which are not exactly known. Reasons for this inexactness are varying meas...
Alexey Pryakhin, Christian Böhm, Matthias Sch...
KDD
2003
ACM
135views Data Mining» more  KDD 2003»
16 years 7 months ago
Efficiently handling feature redundancy in high-dimensional data
High-dimensional data poses a severe challenge for data mining. Feature selection is a frequently used technique in preprocessing high-dimensional data for successful data mining....
Lei Yu, Huan Liu
IBPRIA
2005
Springer
16 years 4 days ago
Gabor Parameter Selection for Local Feature Detection
Abstract. Some recent works have addressed the object recognition problem by representing objects as the composition of independent image parts, where each part is modeled with “...
Plinio Moreno, Alexandre Bernardino, José S...