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» Feature selection in a kernel space
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ICPR
2008
IEEE
14 years 8 months ago
Feature selection focused within error clusters
We propose a feature selection method that constructs each new feature by analysis of tight error clusters. This is a greedy, time-efficient forward selection algorithm that itera...
Henry S. Baird, Sui-Yu Wang
ICRA
2008
IEEE
170views Robotics» more  ICRA 2008»
14 years 2 months ago
Human detection using iterative feature selection and logistic principal component analysis
— We present a fast feature selection algorithm suitable for object detection applications where the image being tested must be scanned repeatedly to detected the object of inter...
Wael Abd-Almageed, Larry S. Davis
ICML
2009
IEEE
14 years 2 months ago
Non-monotonic feature selection
We consider the problem of selecting a subset of m most informative features where m is the number of required features. This feature selection problem is essentially a combinator...
Zenglin Xu, Rong Jin, Jieping Ye, Michael R. Lyu, ...
ML
2010
ACM
181views Machine Learning» more  ML 2010»
13 years 6 months ago
Decomposing the tensor kernel support vector machine for neuroscience data with structured labels
Abstract The tensor kernel has been used across the machine learning literature for a number of purposes and applications, due to its ability to incorporate samples from multiple s...
David R. Hardoon, John Shawe-Taylor
CVPR
2001
IEEE
14 years 9 months ago
Adaptive Quasiconformal Kernel Metric for Image Retrieval
This paper presents a new approach to ranking relevant images for retrieval. Distance in the feature space associated with a kernel is used to rank relevant images. An adaptive qu...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai