Selectivity supervision in combining pattern-recognition modalities by feature- and kernel-selective support vector machines.
Alexander TatarchukVadim MottlAndrey EliseyevDavid WindridgePublished in: ICPR (2008)
Keyphrases
- support vector
- learning machines
- pattern recognition
- kernel function
- large margin classifiers
- kernel methods
- kernel machines
- kernel parameters
- cross validation
- feature selection
- rbf kernel
- svm classification
- support vector machine
- sparse kernel
- maximum margin
- feature maps
- decision function
- svm classifier
- machine learning
- logistic regression
- neural network
- image features
- radial basis function
- computer vision
- classification accuracy
- multiple features
- loss function
- binary classification
- kernel classifiers
- polynomial kernels
- reproducing kernel hilbert space
- feature ranking
- feature space
- hyperplane
- feature subset
- input space
- image processing
- support vector regression
- semi supervised
- dimensionality reduction
- model selection
- kernel matrix
- multi class classification