StyP-Boost: a bilinear boosting algorithm for learning style-parameterized classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style parameters to be introduced to aid classification, where style is any factor which the classes vary with systematically, model...
| Main Authors: | , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
British Machine Vision Association and Society for Pattern Recognition
2010
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