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» A PSO-based framework for dynamic SVM model selection
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GECCO
2009
Springer
118views Optimization» more  GECCO 2009»
13 years 11 months ago
A PSO-based framework for dynamic SVM model selection
Marcelo N. Kapp, Robert Sabourin, Patrick Maupin
ACL
2006
13 years 6 months ago
Semantic Parsing with Structured SVM Ensemble Classification Models
We present a learning framework for structured support vector models in which boosting and bagging methods are used to construct ensemble models. We also propose a selection metho...
Minh Le Nguyen, Akira Shimazu, Xuan Hieu Phan
PAMI
2010
132views more  PAMI 2010»
13 years 3 months ago
Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters
—Adapting the hyperparameters of support vector machines (SVMs) is a challenging model selection problem, especially when flexible kernels are to be adapted and data are scarce....
Tobias Glasmachers, Christian Igel
ICML
2003
IEEE
14 years 5 months ago
Multi-Objective Programming in SVMs
We propose a general framework for support vector machines (SVM) based on the principle of multi-objective optimization. The learning of SVMs is formulated as a multiobjective pro...
Jinbo Bi
CVPR
2012
IEEE
11 years 7 months ago
Part-based multiple-person tracking with partial occlusion handling
Single camera-based multiple-person tracking is often hindered by difficulties such as occlusion and changes in appearance. In this paper, we address such problems by proposing a...
Guang Shu, Afshin Dehghan, Omar Oreifej, Emily Han...