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» Feature selection for ranking using boosted trees
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ICCV
2009
IEEE
15 years 5 months ago
Joint Pose Estimator and Feature Learning for Object Detection
A new learning strategy for object detection is presented. The proposed scheme forgoes the need to train a collection of detectors dedicated to homogeneous families of poses, an...
Karim Ali, Francois Fleuret, David Hasler and Pasc...
ICDM
2002
IEEE
448views Data Mining» more  ICDM 2002»
15 years 4 months ago
Feature Selection Algorithms: A Survey and Experimental Evaluation
In view of the substantial number of existing feature selection algorithms, the need arises to count on criteria that enables to adequately decide which algorithm to use in certai...
Luis Carlos Molina, Lluís Belanche, À...
ICASSP
2008
IEEE
15 years 6 months ago
A comparative study of probabilistic ranking models for spoken document summarization
The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a tar...
Shih-Hsiang Lin, Yi-Ting Chen, Hsin-Min Wang, Bin ...
DIS
2010
Springer
14 years 9 months ago
Sparse Substring Pattern Set Discovery Using Linear Programming Boosting
In this paper, we consider finding a small set of substring patterns which classifies the given documents well. We formulate the problem as 1 norm soft margin optimization problem ...
Kazuaki Kashihara, Kohei Hatano, Hideo Bannai, Mas...
AVBPA
2005
Springer
308views Biometrics» more  AVBPA 2005»
15 years 5 months ago
Biometric Recognition Using Feature Selection and Combination
Most of the prior work in biometric literature has only emphasized on the issue of feature extraction and classification. However, the critical issue of examining the usefulness of...
Ajay Kumar, David Zhang