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ICPR
2006
IEEE
14 years 8 months ago
Boosted Band Ratio Feature Selection for Hyperspectral Image Classification
Band ratios have many useful applications in hyperspectral image analysis. While optimal ratios have been chosen empirically in previous research, we propose a principled algorith...
Antonio Robles-Kelly, Nianjun Liu, Terry Caelli, Z...
IACR
2011
84views more  IACR 2011»
12 years 7 months ago
Tools for Simulating Features of Composite Order Bilinear Groups in the Prime Order Setting
In this paper, we explore a general methodology for converting composite order pairingbased cryptosystems into the prime order setting. We employ the dual pairing vector space app...
Allison B. Lewko
ICML
2007
IEEE
14 years 8 months ago
Supervised feature selection via dependence estimation
We introduce a framework for filtering features that employs the Hilbert-Schmidt Independence Criterion (HSIC) as a measure of dependence between the features and the labels. The ...
Le Song, Alex J. Smola, Arthur Gretton, Karsten M....
TIP
2011
137views more  TIP 2011»
13 years 1 months ago
Boosting Color Feature Selection for Color Face Recognition
—This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boost...
Jae Young Choi, Yong Man Ro, Konstantinos N. Plata...
NIPS
2004
13 years 8 months ago
Result Analysis of the NIPS 2003 Feature Selection Challenge
The NIPS 2003 workshops included a feature selection competition organized by the authors. We provided participants with five datasets from different application domains and calle...
Isabelle Guyon, Steve R. Gunn, Asa Ben-Hur, Gideon...