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» Boosting strategy for classification
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CVPR
2003
IEEE
14 years 11 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
MICCAI
2008
Springer
14 years 10 months ago
AutoGate: Fast and Automatic Doppler Gate Localization in B-Mode Echocardiogram
In this paper, we propose a so-called AutoGate algorithm for fast and automatic Doppler gate localization in B-mode echocardiography. The algorithm has two components: 1) cardiac s...
Jin Hyeong Park, Shaohua Kevin Zhou, Costas Simo...
ICPR
2002
IEEE
14 years 10 months ago
Bayesian Networks as Ensemble of Classifiers
Classification of real-world data poses a number of challenging problems. Mismatch between classifier models and true data distributions on one hand and the use of approximate inf...
Ashutosh Garg, Vladimir Pavlovic, Thomas S. Huang
AUSAI
2008
Springer
13 years 11 months ago
Revisiting Multiple-Instance Learning Via Embedded Instance Selection
Multiple-Instance Learning via Embedded Instance Selection (MILES) is a recently proposed multiple-instance (MI) classification algorithm that applies a single-instance base learne...
James R. Foulds, Eibe Frank
ICASSP
2010
IEEE
13 years 9 months ago
Leveraging evaluation metric-related training criteria for speech summarization
Many of the existing machine-learning approaches to speech summarization cast important sentence selection as a two-class classification problem and have shown empirical success f...
Shih-Hsiang Lin, Yu-Mei Chang, Jia-Wen Liu, Berlin...