Using Low-Rank Approximations to Speed Up Kernel Logistic Regression Algorithm.
Dajiang LeiJianyang TangZhixing LiYu WuPublished in: IEEE Access (2019)
Keyphrases
- regression algorithm
- low rank approximation
- kernel matrix
- semi supervised
- regression methods
- low rank
- kernel methods
- logistic regression
- kernel function
- piecewise linear
- singular value decomposition
- feature space
- metric learning
- iterative algorithms
- support vector
- spectral clustering
- learning algorithm
- support vector machine
- input space
- subspace learning
- model selection
- adjacency matrix
- ls svm
- support vectors
- training samples
- least squares
- feature extraction