Semi-Supervised Kernel Methods for Regression Estimation.
Alexei PozdnoukhovSamy BengioPublished in: ICASSP (5) (2006)
Keyphrases
- kernel methods
- semi supervised
- kernel ridge regression
- reproducing kernel hilbert space
- support vector
- kernel function
- learning problems
- regression algorithm
- kernel matrix
- feature space
- machine learning
- learning tasks
- semi supervised learning
- support vector machine
- kernel machines
- kernel matrices
- mercer kernels
- learning frameworks
- semi parametric
- kernel pca
- multiple kernel learning
- kernel learning
- labeled and unlabeled data
- supervised learning
- model selection
- gradient boosting
- graph kernels
- regression model
- kernel principal component analysis
- multiple kernel
- labeled data
- kernel fisher discriminant analysis
- support vector regression
- learning theory
- density estimation
- loss function
- unlabeled data
- low rank
- subspace learning