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» Stability of Feature Selection Algorithms
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PRL
1998
132views more  PRL 1998»
14 years 11 months ago
Unsupervised feature selection using a neuro-fuzzy approach
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training. The concept of a ¯exible membersh...
Jayanta Basak, Rajat K. De, Sankar K. Pal
ICDM
2005
IEEE
138views Data Mining» more  ICDM 2005»
15 years 5 months ago
On Feature Selection through Clustering
We study an algorithm for feature selection that clusters attributes using a special metric and then makes use of the dendrogram of the resulting cluster hierarchy to choose the m...
Richard Butterworth, Gregory Piatetsky-Shapiro, Da...
ICML
2010
IEEE
15 years 27 days ago
From Transformation-Based Dimensionality Reduction to Feature Selection
Many learning applications are characterized by high dimensions. Usually not all of these dimensions are relevant and some are redundant. There are two main approaches to reduce d...
Mahdokht Masaeli, Glenn Fung, Jennifer G. Dy
CVPR
2006
IEEE
16 years 1 months ago
Joint Boosting Feature Selection for Robust Face Recognition
A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framewo...
Rong Xiao, Wu-Jun Li, Yuandong Tian, Xiaoou Tang
DATE
2010
IEEE
165views Hardware» more  DATE 2010»
15 years 4 months ago
Multicore soft error rate stabilization using adaptive dual modular redundancy
— The use of dynamic voltage and frequency scaling (DVFS) in contemporary multicores provides significant protection from unpredictable thermal events. A side effect of DVFS can ...
Ramakrishna Vadlamani, Jia Zhao, Wayne P. Burleson...