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» Feature selection in a kernel space
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ICPR
2008
IEEE
16 years 1 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»
15 years 6 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
15 years 6 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»
14 years 10 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
16 years 1 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