Subspace based linear programming support vector machines.
Syogo TakeuchiTakuya KitamuraShigeo AbeKazuhiro FukuiPublished in: IJCNN (2009)
Keyphrases
- linear programming
- support vector
- learning machines
- large margin classifiers
- linear program
- kernel function
- principal component analysis
- primal dual
- objective function
- feature space
- support vector machine
- logistic regression
- decision function
- binary classification
- cross validation
- loss function
- multi class
- classification accuracy
- np hard
- low dimensional
- nonlinear programming
- optimal solution
- svm classifier
- dynamic programming
- kernel methods
- feature selection
- generalization ability
- subspace learning
- generalization bounds
- high dimensional
- subspace clustering
- hyperplane
- machine learning
- high dimensional data
- training examples
- soft margin
- dimensionality reduction
- quadratic programming
- learning algorithm
- lower dimensional
- feature extraction
- support vectors
- ls svm
- support vector regression
- integer programming