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KDD
2005
ACM
145views Data Mining» more  KDD 2005»
14 years 12 months ago
Streaming feature selection using alpha-investing
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
ICML
2007
IEEE
15 years 7 days ago
Multiclass multiple kernel learning
In many applications it is desirable to learn from several kernels. "Multiple kernel learning" (MKL) allows the practitioner to optimize over linear combinations of kern...
Alexander Zien, Cheng Soon Ong
ICPR
2004
IEEE
15 years 16 days ago
A Wrapper-Based Approach to Image Segmentation and Classification
The traditional processing flow of segmentation followed by classification in computer vision assumes that the segmentation is able to successfully extract the object of interest....
Anil K. Jain, Michael E. Farmer
ICPR
2006
IEEE
15 years 16 days ago
Feature selection for linear support vector machines
Feature selection is attracted much interest from researchers in many fields such as pattern recognition and data mining. In this paper, a novel algorithm for feature selection is...
Zhizheng Liang, Tuo Zhao
ICIP
2003
IEEE
15 years 1 months ago
Feature selection for unsupervised discovery of statistical temporal structures in video
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
Lexing Xie, Shih-Fu Chang, Ajay Divakaran, Huifang...
ICCV
2003
IEEE
15 years 1 months ago
Conditional Feature Sensitivity: A Unifying View on Active Recognition and Feature Selection
The objective of active recognition is to iteratively collect the next "best" measurements (e.g., camera angles or viewpoints), to maximally reduce ambiguities in recogn...
Xiang Sean Zhou, Dorin Comaniciu, Arun Krishnan
CVPR
2003
IEEE
15 years 1 months ago
Simultaneous Feature Selection and Classifier Training via Linear Programming: A Case Study for Face Expression Recognition
A linear programming technique is introduced that jointly performs feature selection and classifier training so that a subset of features is optimally selected together with the c...
Guodong Guo, Charles R. Dyer